{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 机器学习纳米学位\n",
    "## 非监督学习\n",
    "## 项目 3: 创建用户分类"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "欢迎来到机器学习工程师纳米学位的第三个项目！在这个notebook文件中，有些模板代码已经提供给你，但你还需要实现更多的功能来完成这个项目。除非有明确要求，你无须修改任何已给出的代码。以**'练习'**开始的标题表示接下来的代码部分中有你必须要实现的功能。每一部分都会有详细的指导，需要实现的部分也会在注释中以**'TODO'**标出。请仔细阅读所有的提示！\n",
    "\n",
    "除了实现代码外，你还**必须**回答一些与项目和你的实现有关的问题。每一个需要你回答的问题都会以**'问题 X'**为标题。请仔细阅读每个问题，并且在问题后的**'回答'**文字框中写出完整的答案。我们将根据你对问题的回答和撰写代码所实现的功能来对你提交的项目进行评分。\n",
    "\n",
    ">**提示：**Code 和 Markdown 区域可通过 **Shift + Enter** 快捷键运行。此外，Markdown可以通过双击进入编辑模式。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 开始\n",
    "\n",
    "在这个项目中，你将分析一个数据集的内在结构，这个数据集包含很多客户真对不同类型产品的年度采购额（用**金额**表示）。这个项目的任务之一是如何最好地描述一个批发商不同种类顾客之间的差异。这样做将能够使得批发商能够更好的组织他们的物流服务以满足每个客户的需求。\n",
    "\n",
    "这个项目的数据集能够在[UCI机器学习信息库](https://archive.ics.uci.edu/ml/datasets/Wholesale+customers)中找到.因为这个项目的目的，分析将不会包括'Channel'和'Region'这两个特征——重点集中在6个记录的客户购买的产品类别上。\n",
    "\n",
    "运行下面的的代码单元以载入整个客户数据集和一些这个项目需要的Python库。如果你的数据集载入成功，你将看到后面输出数据集的大小。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# 检查你的Python版本\n",
    "from sys import version_info\n",
    "if version_info.major != 2 and version_info.minor != 7:\n",
    "    raise Exception('请使用Python 2.7来完成此项目')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Wholesale customers dataset has 440 samples with 6 features each.\n"
     ]
    }
   ],
   "source": [
    "# 引入这个项目需要的库\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import visuals as vs\n",
    "from IPython.display import display # 使得我们可以对DataFrame使用display()函数\n",
    "\n",
    "# 设置以内联的形式显示matplotlib绘制的图片（在notebook中显示更美观）\n",
    "%matplotlib inline\n",
    "\n",
    "# 载入整个客户数据集\n",
    "try:\n",
    "    data = pd.read_csv(\"customers.csv\")\n",
    "    data.drop(['Region', 'Channel'], axis = 1, inplace = True)\n",
    "    print \"Wholesale customers dataset has {} samples with {} features each.\".format(*data.shape)\n",
    "except:\n",
    "    print \"Dataset could not be loaded. Is the dataset missing?\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 分析数据\n",
    "在这部分，你将开始分析数据，通过可视化和代码来理解每一个特征和其他特征的联系。你会看到关于数据集的统计描述，考虑每一个属性的相关性，然后从数据集中选择若干个样本数据点，你将在整个项目中一直跟踪研究这几个数据点。\n",
    "\n",
    "运行下面的代码单元给出数据集的一个统计描述。注意这个数据集包含了6个重要的产品类型：**'Fresh'**, **'Milk'**, **'Grocery'**, **'Frozen'**, **'Detergents_Paper'**和 **'Delicatessen'**。想一下这里每一个类型代表你会购买什么样的产品。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Fresh</th>\n",
       "      <th>Milk</th>\n",
       "      <th>Grocery</th>\n",
       "      <th>Frozen</th>\n",
       "      <th>Detergents_Paper</th>\n",
       "      <th>Delicatessen</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>440.000000</td>\n",
       "      <td>440.000000</td>\n",
       "      <td>440.000000</td>\n",
       "      <td>440.000000</td>\n",
       "      <td>440.000000</td>\n",
       "      <td>440.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>12000.297727</td>\n",
       "      <td>5796.265909</td>\n",
       "      <td>7951.277273</td>\n",
       "      <td>3071.931818</td>\n",
       "      <td>2881.493182</td>\n",
       "      <td>1524.870455</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>12647.328865</td>\n",
       "      <td>7380.377175</td>\n",
       "      <td>9503.162829</td>\n",
       "      <td>4854.673333</td>\n",
       "      <td>4767.854448</td>\n",
       "      <td>2820.105937</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>3.000000</td>\n",
       "      <td>55.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>25.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>3.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>3127.750000</td>\n",
       "      <td>1533.000000</td>\n",
       "      <td>2153.000000</td>\n",
       "      <td>742.250000</td>\n",
       "      <td>256.750000</td>\n",
       "      <td>408.250000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>8504.000000</td>\n",
       "      <td>3627.000000</td>\n",
       "      <td>4755.500000</td>\n",
       "      <td>1526.000000</td>\n",
       "      <td>816.500000</td>\n",
       "      <td>965.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>16933.750000</td>\n",
       "      <td>7190.250000</td>\n",
       "      <td>10655.750000</td>\n",
       "      <td>3554.250000</td>\n",
       "      <td>3922.000000</td>\n",
       "      <td>1820.250000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>112151.000000</td>\n",
       "      <td>73498.000000</td>\n",
       "      <td>92780.000000</td>\n",
       "      <td>60869.000000</td>\n",
       "      <td>40827.000000</td>\n",
       "      <td>47943.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               Fresh          Milk       Grocery        Frozen  \\\n",
       "count     440.000000    440.000000    440.000000    440.000000   \n",
       "mean    12000.297727   5796.265909   7951.277273   3071.931818   \n",
       "std     12647.328865   7380.377175   9503.162829   4854.673333   \n",
       "min         3.000000     55.000000      3.000000     25.000000   \n",
       "25%      3127.750000   1533.000000   2153.000000    742.250000   \n",
       "50%      8504.000000   3627.000000   4755.500000   1526.000000   \n",
       "75%     16933.750000   7190.250000  10655.750000   3554.250000   \n",
       "max    112151.000000  73498.000000  92780.000000  60869.000000   \n",
       "\n",
       "       Detergents_Paper  Delicatessen  \n",
       "count        440.000000    440.000000  \n",
       "mean        2881.493182   1524.870455  \n",
       "std         4767.854448   2820.105937  \n",
       "min            3.000000      3.000000  \n",
       "25%          256.750000    408.250000  \n",
       "50%          816.500000    965.500000  \n",
       "75%         3922.000000   1820.250000  \n",
       "max        40827.000000  47943.000000  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 显示数据集的一个描述\n",
    "display(data.describe())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 练习: 选择样本\n",
    "为了对客户有一个更好的了解，并且了解代表他们的数据将会在这个分析过程中如何变换。最好是选择几个样本数据点，并且更为详细地分析它们。在下面的代码单元中，选择**三个**索引加入到索引列表`indices`中，这三个索引代表你要追踪的客户。我们建议你不断尝试，直到找到三个明显不同的客户。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Chosen samples of wholesale customers dataset:\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Fresh</th>\n",
       "      <th>Milk</th>\n",
       "      <th>Grocery</th>\n",
       "      <th>Frozen</th>\n",
       "      <th>Detergents_Paper</th>\n",
       "      <th>Delicatessen</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>36050</td>\n",
       "      <td>1642</td>\n",
       "      <td>2961</td>\n",
       "      <td>4787</td>\n",
       "      <td>500</td>\n",
       "      <td>1621</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1838</td>\n",
       "      <td>6380</td>\n",
       "      <td>2824</td>\n",
       "      <td>1218</td>\n",
       "      <td>1216</td>\n",
       "      <td>295</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3136</td>\n",
       "      <td>8630</td>\n",
       "      <td>13586</td>\n",
       "      <td>5641</td>\n",
       "      <td>4666</td>\n",
       "      <td>1426</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Fresh  Milk  Grocery  Frozen  Detergents_Paper  Delicatessen\n",
       "0  36050  1642     2961    4787               500          1621\n",
       "1   1838  6380     2824    1218              1216           295\n",
       "2   3136  8630    13586    5641              4666          1426"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# TODO：从数据集中选择三个你希望抽样的数据点的索引\n",
    "indices = [124, 235, 376]\n",
    "\n",
    "# 为选择的样本建立一个DataFrame\n",
    "samples = pd.DataFrame(data.loc[indices], columns = data.keys()).reset_index(drop = True)\n",
    "print \"Chosen samples of wholesale customers dataset:\"\n",
    "display(samples)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 问题 1\n",
    "*在你看来你选择的这三个样本点分别代表什么类型的企业（客户）？*对每一个你选择的样本客户，通过它在每一种产品类型上的花费与数据集的统计描述进行比较，给出你做上述判断的理由。\n",
    "\n",
    "\n",
    "**提示：** 企业的类型包括超市、咖啡馆、零售商以及其他。注意不要使用具体企业的名字，比如说在描述一个餐饮业客户时，你不能使用麦当劳。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**回答:**\n",
    "\n",
    "1. 饭店：Fresh、Frozen超过75%分位点，Delicatessen也只是略低于75%分位点，这些都是食材，Milk、Grocery、Detergents_Paper都在50%分位点以下，所以推测这是一个饭店。\n",
    "\n",
    "2. 咖啡店：Milk将近75%分位点，应该是冲调咖啡用；Detergents_Paper超过了50%分位点，应该是清理少量泼洒的饮料；Fresh、Grocery、Frozen、Delicatessen都在50%分位点以下，应该只是提供的少量食品，所以推测是咖啡店。\n",
    "\n",
    "3. 超市：Milk、Grocery、Frozen、Detergents_Paper都在75%分位点以上，Delicatessen也接近75%分位点，说明多种商品需求量都很大，Fresh在25%分位点左右，应该是由于Fresh保质期短，超市不方便大量出售，所以推测是超市。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 练习: 特征相关性\n",
    "一个有趣的想法是，考虑这六个类别中的一个（或者多个）产品类别，是否对于理解客户的购买行为具有实际的相关性。也就是说，当用户购买了一定数量的某一类产品，我们是否能够确定他们必然会成比例地购买另一种类的产品。有一个简单的方法可以检测相关性：我们用移除了某一个特征之后的数据集来构建一个监督学习（回归）模型，然后用这个模型去预测那个被移除的特征，再对这个预测结果进行评分，看看预测结果如何。\n",
    "\n",
    "在下面的代码单元中，你需要实现以下的功能：\n",
    " - 使用`DataFrame.drop`函数移除数据集中你选择的不需要的特征，并将移除后的结果赋值给`new_data`。\n",
    " - 使用`sklearn.model_selection.train_test_split`将数据集分割成训练集和测试集。\n",
    "   - 使用移除的特征作为你的目标标签。设置`test_size`为`0.25`并设置一个`random_state`。\n",
    " - 导入一个DecisionTreeRegressor（决策树回归器），设置一个`random_state`，然后用训练集训练它。\n",
    " - 使用回归器的`score`函数输出模型在测试集上的预测得分。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.809546749472\n"
     ]
    }
   ],
   "source": [
    "# TODO：为DataFrame创建一个副本，用'drop'函数丢弃一个特征\n",
    "new_data = data.copy().drop(['Grocery'], axis = 1)\n",
    "\n",
    "from sklearn.model_selection import train_test_split\n",
    "# TODO：使用给定的特征作为目标，将数据分割成训练集和测试集\n",
    "X_train, X_test, y_train, y_test = train_test_split(new_data, data['Grocery'], test_size = 0.25, random_state = 12)\n",
    "\n",
    "from sklearn.tree import DecisionTreeRegressor\n",
    "# TODO：创建一个DecisionTreeRegressor（决策树回归器）并在训练集上训练它\n",
    "regressor = DecisionTreeRegressor(random_state = 23)\n",
    "regressor.fit(X_train, y_train)\n",
    "\n",
    "# TODO：输出在测试集上的预测得分\n",
    "score = regressor.score(X_test, y_test)\n",
    "print score"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 问题 2\n",
    "*你尝试预测哪一个特征？预测的得分是多少？这个特征对于区分用户的消费习惯来说必要吗？为什么？*  \n",
    "**提示：** 决定系数（coefficient of determination）, `R^2`,结果在0到1之间，1表示完美拟合，一个负的`R^2`表示模型不能够拟合数据。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**回答:**\n",
    "\n",
    "我尝试预测 Grocery 特征，预测的得分是0.8095。这个特征对于区分用户的消费习惯来说没有太大必要，因为决定系数达到了0.8，说明用其他特征来拟合 Grocery 特别好，也就是说 Grocery 可以由其他特征推得，因此没有必要。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 可视化特征分布\n",
    "为了能够对这个数据集有一个更好的理解，我们可以对数据集中的每一个产品特征构建一个散布矩阵（scatter matrix）。如果你发现你在上面尝试预测的特征对于区分一个特定的用户来说是必须的，那么这个特征和其它的特征可能不会在下面的散射矩阵中显示任何关系。相反的，如果你认为这个特征对于识别一个特定的客户是没有作用的，那么通过散布矩阵可以看出在这个数据特征和其它特征中有关联性。运行下面的代码以创建一个散布矩阵。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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ob+UL3Z3UsD2klLSckJbrM7nU4tvnlrhcbTNb7eBLSRBGN8lHh7JYukYowQ2i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\njuM4juM4juM4U+T/A4QlrUkuXgO6AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f5e7c47c550>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 对于数据中的每一对特征构造一个散布矩阵\n",
    "pd.plotting.scatter_matrix(data, alpha = 0.3, figsize = (14,8), diagonal = 'kde');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 问题 3\n",
    "*这里是否存在一些特征他们彼此之间存在一定程度相关性？如果有请列出。这个结果是验证了还是否认了你尝试预测的那个特征的相关性？这些特征的数据是怎么分布的？*\n",
    "\n",
    "**提示：** 这些数据是正态分布(normally distributed)的吗？大多数的数据点分布在哪？"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**回答:**\n",
    "\n",
    "Grocery 和 Milk，Grocery 和 Detergents_Paper 存在一定程度相关性。\n",
    "\n",
    "这个结果验证了我尝试预测的那个特征的相关性，因为Milk和Detergents_Paper都与Grocery相关。\n",
    "\n",
    "从矩阵对角线上的图来看，这些特征的左右并不对称，因此不服从正态分布，普遍右侧长、左侧短，因此服从正偏态分布，大多数的数据点分布在左侧。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 数据预处理\n",
    "在这个部分，你将通过在数据上做一个合适的缩放，并检测异常点（你可以选择性移除）将数据预处理成一个更好的代表客户的形式。预处理数据是保证你在分析中能够得到显著且有意义的结果的重要环节。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 练习: 特征缩放\n",
    "如果数据不是正态分布的，尤其是数据的平均数和中位数相差很大的时候（表示数据非常歪斜）。这时候通常用一个非线性的缩放是[很合适的](https://github.com/czcbangkai/translations/blob/master/use_of_logarithms_in_economics/use_of_logarithms_in_economics.pdf)，[（英文原文）](http://econbrowser.com/archives/2014/02/use-of-logarithms-in-economics) — 尤其是对于金融数据。一种实现这个缩放的方法是使用[Box-Cox 变换](http://scipy.github.io/devdocs/generated/scipy.stats.boxcox.html)，这个方法能够计算出能够最佳减小数据倾斜的指数变换方法。一个比较简单的并且在大多数情况下都适用的方法是使用自然对数。\n",
    "\n",
    "在下面的代码单元中，你将需要实现以下功能：\n",
    " - 使用`np.log`函数在数据 `data` 上做一个对数缩放，然后将它的副本（不改变原始data的值）赋值给`log_data`。\n",
    " - 使用`np.log`函数在样本数据 `samples` 上做一个对数缩放，然后将它的副本赋值给`log_samples`。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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SztmtrB+YNKWc0xDFkHN1k6EXMVlQUUSBN1e6uEFMnKScWq5xpWURxSmWH1PQ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\ntJ6jbGmstT3ypgiivLozoGjp2IbCjUafG7siNf7SVg9NkXl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YUB3RBo9O5Li82UNVJJpu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eb5n2PvM0byT3CjsR/MwBR4FPAJ8UQpxd/ZdCiJ8QQrwphHhzaWlpB4bXZbOE6kRF3r5T4nJb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RZ5XeGFg3XObA2IRlxSRZIoWxq1vM5c+daUl5KpcWJ+v+/FrSYRPyw8t1zDCUUX7m4wWTJx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\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4rZgWypLE8f7kliQn50pWS5rx5OD1S+iFmtMKstpsA1KYLZrM10lHtR07sKt2uEZKDY/p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\n7bBvIMWpKzU8X9KyXbJJlcurHZ47WubCcnSg8KXkw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w0IWtQn4fZtXaFoaULqNffhpmm/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\nYDAYDAaDwWDYEPz/mX9ycZaHgI0AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f5e435c6710>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# TODO：使用自然对数缩放数据\n",
    "log_data = np.log(data)\n",
    "\n",
    "# TODO：使用自然对数缩放样本数据\n",
    "log_samples = np.log(samples)\n",
    "\n",
    "# 为每一对新产生的特征制作一个散射矩阵\n",
    "pd.plotting.scatter_matrix(log_data, alpha = 0.3, figsize = (14,8), diagonal = 'kde');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 观察\n",
    "在使用了一个自然对数的缩放之后，数据的各个特征会显得更加的正态分布。对于任意的你以前发现有相关关系的特征对，观察他们的相关关系是否还是存在的（并且尝试观察，他们的相关关系相比原来是变强了还是变弱了）。\n",
    "\n",
    "运行下面的代码以观察样本数据在进行了自然对数转换之后如何改变了。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
       "    .dataframe thead th {\n",
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       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Fresh</th>\n",
       "      <th>Milk</th>\n",
       "      <th>Grocery</th>\n",
       "      <th>Frozen</th>\n",
       "      <th>Detergents_Paper</th>\n",
       "      <th>Delicatessen</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>10.492662</td>\n",
       "      <td>7.403670</td>\n",
       "      <td>7.993282</td>\n",
       "      <td>8.473659</td>\n",
       "      <td>6.214608</td>\n",
       "      <td>7.390799</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>7.516433</td>\n",
       "      <td>8.760923</td>\n",
       "      <td>7.945910</td>\n",
       "      <td>7.104965</td>\n",
       "      <td>7.103322</td>\n",
       "      <td>5.686975</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>8.050703</td>\n",
       "      <td>9.063000</td>\n",
       "      <td>9.516795</td>\n",
       "      <td>8.637817</td>\n",
       "      <td>8.448057</td>\n",
       "      <td>7.262629</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       Fresh      Milk   Grocery    Frozen  Detergents_Paper  Delicatessen\n",
       "0  10.492662  7.403670  7.993282  8.473659          6.214608      7.390799\n",
       "1   7.516433  8.760923  7.945910  7.104965          7.103322      5.686975\n",
       "2   8.050703  9.063000  9.516795  8.637817          8.448057      7.262629"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 展示经过对数变换后的样本数据\n",
    "display(log_samples)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 练习: 异常值检测\n",
    "对于任何的分析，在数据预处理的过程中检测数据中的异常值都是非常重要的一步。异常值的出现会使得把这些值考虑进去后结果出现倾斜。这里有很多关于怎样定义什么是数据集中的异常值的经验法则。这里我们将使用[Tukey的定义异常值的方法](http://datapigtechnologies.com/blog/index.php/highlighting-outliers-in-your-data-with-the-tukey-method/)：一个*异常阶（outlier step）*被定义成1.5倍的四分位距（interquartile range，IQR）。一个数据点如果某个特征包含在该特征的IQR之外的特征，那么该数据点被认定为异常点。\n",
    "\n",
    "在下面的代码单元中，你需要完成下面的功能：\n",
    " - 将指定特征的25th分位点的值分配给`Q1`。使用`np.percentile`来完成这个功能。\n",
    " - 将指定特征的75th分位点的值分配给`Q3`。同样的，使用`np.percentile`来完成这个功能。\n",
    " - 将指定特征的异常阶的计算结果赋值给`step`.\n",
    " - 选择性地通过将索引添加到`outliers`列表中，以移除异常值。\n",
    "\n",
    "**注意：** 如果你选择移除异常值，请保证你选择的样本点不在这些移除的点当中！\n",
    "一旦你完成了这些功能，数据集将存储在`good_data`中。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Data points considered outliers for the feature 'Fresh':\n"
     ]
    },
    {
     "data": {
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       "      <th></th>\n",
       "      <th>Fresh</th>\n",
       "      <th>Milk</th>\n",
       "      <th>Grocery</th>\n",
       "      <th>Frozen</th>\n",
       "      <th>Detergents_Paper</th>\n",
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       "  <tbody>\n",
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       "      <th>65</th>\n",
       "      <td>4.442651</td>\n",
       "      <td>9.950323</td>\n",
       "      <td>10.732651</td>\n",
       "      <td>3.583519</td>\n",
       "      <td>10.095388</td>\n",
       "      <td>7.260523</td>\n",
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       "    <tr>\n",
       "      <th>66</th>\n",
       "      <td>2.197225</td>\n",
       "      <td>7.335634</td>\n",
       "      <td>8.911530</td>\n",
       "      <td>5.164786</td>\n",
       "      <td>8.151333</td>\n",
       "      <td>3.295837</td>\n",
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       "    <tr>\n",
       "      <th>81</th>\n",
       "      <td>5.389072</td>\n",
       "      <td>9.163249</td>\n",
       "      <td>9.575192</td>\n",
       "      <td>5.645447</td>\n",
       "      <td>8.964184</td>\n",
       "      <td>5.049856</td>\n",
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       "    <tr>\n",
       "      <th>95</th>\n",
       "      <td>1.098612</td>\n",
       "      <td>7.979339</td>\n",
       "      <td>8.740657</td>\n",
       "      <td>6.086775</td>\n",
       "      <td>5.407172</td>\n",
       "      <td>6.563856</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>96</th>\n",
       "      <td>3.135494</td>\n",
       "      <td>7.869402</td>\n",
       "      <td>9.001839</td>\n",
       "      <td>4.976734</td>\n",
       "      <td>8.262043</td>\n",
       "      <td>5.379897</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>128</th>\n",
       "      <td>4.941642</td>\n",
       "      <td>9.087834</td>\n",
       "      <td>8.248791</td>\n",
       "      <td>4.955827</td>\n",
       "      <td>6.967909</td>\n",
       "      <td>1.098612</td>\n",
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       "    <tr>\n",
       "      <th>171</th>\n",
       "      <td>5.298317</td>\n",
       "      <td>10.160530</td>\n",
       "      <td>9.894245</td>\n",
       "      <td>6.478510</td>\n",
       "      <td>9.079434</td>\n",
       "      <td>8.740337</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>193</th>\n",
       "      <td>5.192957</td>\n",
       "      <td>8.156223</td>\n",
       "      <td>9.917982</td>\n",
       "      <td>6.865891</td>\n",
       "      <td>8.633731</td>\n",
       "      <td>6.501290</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>218</th>\n",
       "      <td>2.890372</td>\n",
       "      <td>8.923191</td>\n",
       "      <td>9.629380</td>\n",
       "      <td>7.158514</td>\n",
       "      <td>8.475746</td>\n",
       "      <td>8.759669</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>304</th>\n",
       "      <td>5.081404</td>\n",
       "      <td>8.917311</td>\n",
       "      <td>10.117510</td>\n",
       "      <td>6.424869</td>\n",
       "      <td>9.374413</td>\n",
       "      <td>7.787382</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>305</th>\n",
       "      <td>5.493061</td>\n",
       "      <td>9.468001</td>\n",
       "      <td>9.088399</td>\n",
       "      <td>6.683361</td>\n",
       "      <td>8.271037</td>\n",
       "      <td>5.351858</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>338</th>\n",
       "      <td>1.098612</td>\n",
       "      <td>5.808142</td>\n",
       "      <td>8.856661</td>\n",
       "      <td>9.655090</td>\n",
       "      <td>2.708050</td>\n",
       "      <td>6.309918</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>353</th>\n",
       "      <td>4.762174</td>\n",
       "      <td>8.742574</td>\n",
       "      <td>9.961898</td>\n",
       "      <td>5.429346</td>\n",
       "      <td>9.069007</td>\n",
       "      <td>7.013016</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>355</th>\n",
       "      <td>5.247024</td>\n",
       "      <td>6.588926</td>\n",
       "      <td>7.606885</td>\n",
       "      <td>5.501258</td>\n",
       "      <td>5.214936</td>\n",
       "      <td>4.844187</td>\n",
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       "    <tr>\n",
       "      <th>357</th>\n",
       "      <td>3.610918</td>\n",
       "      <td>7.150701</td>\n",
       "      <td>10.011086</td>\n",
       "      <td>4.919981</td>\n",
       "      <td>8.816853</td>\n",
       "      <td>4.700480</td>\n",
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       "    <tr>\n",
       "      <th>412</th>\n",
       "      <td>4.574711</td>\n",
       "      <td>8.190077</td>\n",
       "      <td>9.425452</td>\n",
       "      <td>4.584967</td>\n",
       "      <td>7.996317</td>\n",
       "      <td>4.127134</td>\n",
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       "        Fresh       Milk    Grocery    Frozen  Detergents_Paper  Delicatessen\n",
       "65   4.442651   9.950323  10.732651  3.583519         10.095388      7.260523\n",
       "66   2.197225   7.335634   8.911530  5.164786          8.151333      3.295837\n",
       "81   5.389072   9.163249   9.575192  5.645447          8.964184      5.049856\n",
       "95   1.098612   7.979339   8.740657  6.086775          5.407172      6.563856\n",
       "96   3.135494   7.869402   9.001839  4.976734          8.262043      5.379897\n",
       "128  4.941642   9.087834   8.248791  4.955827          6.967909      1.098612\n",
       "171  5.298317  10.160530   9.894245  6.478510          9.079434      8.740337\n",
       "193  5.192957   8.156223   9.917982  6.865891          8.633731      6.501290\n",
       "218  2.890372   8.923191   9.629380  7.158514          8.475746      8.759669\n",
       "304  5.081404   8.917311  10.117510  6.424869          9.374413      7.787382\n",
       "305  5.493061   9.468001   9.088399  6.683361          8.271037      5.351858\n",
       "338  1.098612   5.808142   8.856661  9.655090          2.708050      6.309918\n",
       "353  4.762174   8.742574   9.961898  5.429346          9.069007      7.013016\n",
       "355  5.247024   6.588926   7.606885  5.501258          5.214936      4.844187\n",
       "357  3.610918   7.150701  10.011086  4.919981          8.816853      4.700480\n",
       "412  4.574711   8.190077   9.425452  4.584967          7.996317      4.127134"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Data points considered outliers for the feature 'Milk':\n"
     ]
    },
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       "    <tr>\n",
       "      <th>98</th>\n",
       "      <td>6.220590</td>\n",
       "      <td>4.718499</td>\n",
       "      <td>6.656727</td>\n",
       "      <td>6.796824</td>\n",
       "      <td>4.025352</td>\n",
       "      <td>4.882802</td>\n",
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       "      <th>154</th>\n",
       "      <td>6.432940</td>\n",
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       "      <td>4.919981</td>\n",
       "      <td>4.317488</td>\n",
       "      <td>1.945910</td>\n",
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       "      <th>356</th>\n",
       "      <td>10.029503</td>\n",
       "      <td>4.897840</td>\n",
       "      <td>5.384495</td>\n",
       "      <td>8.057377</td>\n",
       "      <td>2.197225</td>\n",
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       "         Fresh       Milk    Grocery    Frozen  Detergents_Paper  Delicatessen\n",
       "86   10.039983  11.205013  10.377047  6.894670          9.906981      6.805723\n",
       "98    6.220590   4.718499   6.656727  6.796824          4.025352      4.882802\n",
       "154   6.432940   4.007333   4.919981  4.317488          1.945910      2.079442\n",
       "356  10.029503   4.897840   5.384495  8.057377          2.197225      6.306275"
      ]
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     "text": [
      "Data points considered outliers for the feature 'Grocery':\n"
     ]
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       "      <th>75</th>\n",
       "      <td>9.923192</td>\n",
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       "      <td>1.098612</td>\n",
       "      <td>8.390949</td>\n",
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       "      <th>154</th>\n",
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       "        Fresh      Milk   Grocery    Frozen  Detergents_Paper  Delicatessen\n",
       "75   9.923192  7.036148  1.098612  8.390949          1.098612      6.882437\n",
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      ]
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     "metadata": {},
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    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Data points considered outliers for the feature 'Frozen':\n"
     ]
    },
    {
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       "      <th>38</th>\n",
       "      <td>8.431853</td>\n",
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       "      <td>6.070738</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>57</th>\n",
       "      <td>8.597297</td>\n",
       "      <td>9.203618</td>\n",
       "      <td>9.257892</td>\n",
       "      <td>3.637586</td>\n",
       "      <td>8.932213</td>\n",
       "      <td>7.156177</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>65</th>\n",
       "      <td>4.442651</td>\n",
       "      <td>9.950323</td>\n",
       "      <td>10.732651</td>\n",
       "      <td>3.583519</td>\n",
       "      <td>10.095388</td>\n",
       "      <td>7.260523</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>145</th>\n",
       "      <td>10.000569</td>\n",
       "      <td>9.034080</td>\n",
       "      <td>10.457143</td>\n",
       "      <td>3.737670</td>\n",
       "      <td>9.440738</td>\n",
       "      <td>8.396155</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>175</th>\n",
       "      <td>7.759187</td>\n",
       "      <td>8.967632</td>\n",
       "      <td>9.382106</td>\n",
       "      <td>3.951244</td>\n",
       "      <td>8.341887</td>\n",
       "      <td>7.436617</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>264</th>\n",
       "      <td>6.978214</td>\n",
       "      <td>9.177714</td>\n",
       "      <td>9.645041</td>\n",
       "      <td>4.110874</td>\n",
       "      <td>8.696176</td>\n",
       "      <td>7.142827</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>325</th>\n",
       "      <td>10.395650</td>\n",
       "      <td>9.728181</td>\n",
       "      <td>9.519735</td>\n",
       "      <td>11.016479</td>\n",
       "      <td>7.148346</td>\n",
       "      <td>8.632128</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>420</th>\n",
       "      <td>8.402007</td>\n",
       "      <td>8.569026</td>\n",
       "      <td>9.490015</td>\n",
       "      <td>3.218876</td>\n",
       "      <td>8.827321</td>\n",
       "      <td>7.239215</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>429</th>\n",
       "      <td>9.060331</td>\n",
       "      <td>7.467371</td>\n",
       "      <td>8.183118</td>\n",
       "      <td>3.850148</td>\n",
       "      <td>4.430817</td>\n",
       "      <td>7.824446</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>439</th>\n",
       "      <td>7.932721</td>\n",
       "      <td>7.437206</td>\n",
       "      <td>7.828038</td>\n",
       "      <td>4.174387</td>\n",
       "      <td>6.167516</td>\n",
       "      <td>3.951244</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         Fresh      Milk    Grocery     Frozen  Detergents_Paper  Delicatessen\n",
       "38    8.431853  9.663261   9.723703   3.496508          8.847360      6.070738\n",
       "57    8.597297  9.203618   9.257892   3.637586          8.932213      7.156177\n",
       "65    4.442651  9.950323  10.732651   3.583519         10.095388      7.260523\n",
       "145  10.000569  9.034080  10.457143   3.737670          9.440738      8.396155\n",
       "175   7.759187  8.967632   9.382106   3.951244          8.341887      7.436617\n",
       "264   6.978214  9.177714   9.645041   4.110874          8.696176      7.142827\n",
       "325  10.395650  9.728181   9.519735  11.016479          7.148346      8.632128\n",
       "420   8.402007  8.569026   9.490015   3.218876          8.827321      7.239215\n",
       "429   9.060331  7.467371   8.183118   3.850148          4.430817      7.824446\n",
       "439   7.932721  7.437206   7.828038   4.174387          6.167516      3.951244"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Data points considered outliers for the feature 'Detergents_Paper':\n"
     ]
    },
    {
     "data": {
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       "      <th>Fresh</th>\n",
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       "    <tr>\n",
       "      <th>75</th>\n",
       "      <td>9.923192</td>\n",
       "      <td>7.036148</td>\n",
       "      <td>1.098612</td>\n",
       "      <td>8.390949</td>\n",
       "      <td>1.098612</td>\n",
       "      <td>6.882437</td>\n",
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       "    <tr>\n",
       "      <th>161</th>\n",
       "      <td>9.428190</td>\n",
       "      <td>6.291569</td>\n",
       "      <td>5.645447</td>\n",
       "      <td>6.995766</td>\n",
       "      <td>1.098612</td>\n",
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       "        Fresh      Milk   Grocery    Frozen  Detergents_Paper  Delicatessen\n",
       "75   9.923192  7.036148  1.098612  8.390949          1.098612      6.882437\n",
       "161  9.428190  6.291569  5.645447  6.995766          1.098612      7.711101"
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     "text": [
      "Data points considered outliers for the feature 'Delicatessen':\n"
     ]
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       "      <th>Fresh</th>\n",
       "      <th>Milk</th>\n",
       "      <th>Grocery</th>\n",
       "      <th>Frozen</th>\n",
       "      <th>Detergents_Paper</th>\n",
       "      <th>Delicatessen</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>66</th>\n",
       "      <td>2.197225</td>\n",
       "      <td>7.335634</td>\n",
       "      <td>8.911530</td>\n",
       "      <td>5.164786</td>\n",
       "      <td>8.151333</td>\n",
       "      <td>3.295837</td>\n",
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       "    <tr>\n",
       "      <th>109</th>\n",
       "      <td>7.248504</td>\n",
       "      <td>9.724899</td>\n",
       "      <td>10.274568</td>\n",
       "      <td>6.511745</td>\n",
       "      <td>6.728629</td>\n",
       "      <td>1.098612</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>128</th>\n",
       "      <td>4.941642</td>\n",
       "      <td>9.087834</td>\n",
       "      <td>8.248791</td>\n",
       "      <td>4.955827</td>\n",
       "      <td>6.967909</td>\n",
       "      <td>1.098612</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>137</th>\n",
       "      <td>8.034955</td>\n",
       "      <td>8.997147</td>\n",
       "      <td>9.021840</td>\n",
       "      <td>6.493754</td>\n",
       "      <td>6.580639</td>\n",
       "      <td>3.583519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>142</th>\n",
       "      <td>10.519646</td>\n",
       "      <td>8.875147</td>\n",
       "      <td>9.018332</td>\n",
       "      <td>8.004700</td>\n",
       "      <td>2.995732</td>\n",
       "      <td>1.098612</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>154</th>\n",
       "      <td>6.432940</td>\n",
       "      <td>4.007333</td>\n",
       "      <td>4.919981</td>\n",
       "      <td>4.317488</td>\n",
       "      <td>1.945910</td>\n",
       "      <td>2.079442</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>183</th>\n",
       "      <td>10.514529</td>\n",
       "      <td>10.690808</td>\n",
       "      <td>9.911952</td>\n",
       "      <td>10.505999</td>\n",
       "      <td>5.476464</td>\n",
       "      <td>10.777768</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>184</th>\n",
       "      <td>5.789960</td>\n",
       "      <td>6.822197</td>\n",
       "      <td>8.457443</td>\n",
       "      <td>4.304065</td>\n",
       "      <td>5.811141</td>\n",
       "      <td>2.397895</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>187</th>\n",
       "      <td>7.798933</td>\n",
       "      <td>8.987447</td>\n",
       "      <td>9.192075</td>\n",
       "      <td>8.743372</td>\n",
       "      <td>8.148735</td>\n",
       "      <td>1.098612</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>203</th>\n",
       "      <td>6.368187</td>\n",
       "      <td>6.529419</td>\n",
       "      <td>7.703459</td>\n",
       "      <td>6.150603</td>\n",
       "      <td>6.860664</td>\n",
       "      <td>2.890372</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>233</th>\n",
       "      <td>6.871091</td>\n",
       "      <td>8.513988</td>\n",
       "      <td>8.106515</td>\n",
       "      <td>6.842683</td>\n",
       "      <td>6.013715</td>\n",
       "      <td>1.945910</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>285</th>\n",
       "      <td>10.602965</td>\n",
       "      <td>6.461468</td>\n",
       "      <td>8.188689</td>\n",
       "      <td>6.948897</td>\n",
       "      <td>6.077642</td>\n",
       "      <td>2.890372</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>289</th>\n",
       "      <td>10.663966</td>\n",
       "      <td>5.655992</td>\n",
       "      <td>6.154858</td>\n",
       "      <td>7.235619</td>\n",
       "      <td>3.465736</td>\n",
       "      <td>3.091042</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>343</th>\n",
       "      <td>7.431892</td>\n",
       "      <td>8.848509</td>\n",
       "      <td>10.177932</td>\n",
       "      <td>7.283448</td>\n",
       "      <td>9.646593</td>\n",
       "      <td>3.610918</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         Fresh       Milk    Grocery     Frozen  Detergents_Paper  \\\n",
       "66    2.197225   7.335634   8.911530   5.164786          8.151333   \n",
       "109   7.248504   9.724899  10.274568   6.511745          6.728629   \n",
       "128   4.941642   9.087834   8.248791   4.955827          6.967909   \n",
       "137   8.034955   8.997147   9.021840   6.493754          6.580639   \n",
       "142  10.519646   8.875147   9.018332   8.004700          2.995732   \n",
       "154   6.432940   4.007333   4.919981   4.317488          1.945910   \n",
       "183  10.514529  10.690808   9.911952  10.505999          5.476464   \n",
       "184   5.789960   6.822197   8.457443   4.304065          5.811141   \n",
       "187   7.798933   8.987447   9.192075   8.743372          8.148735   \n",
       "203   6.368187   6.529419   7.703459   6.150603          6.860664   \n",
       "233   6.871091   8.513988   8.106515   6.842683          6.013715   \n",
       "285  10.602965   6.461468   8.188689   6.948897          6.077642   \n",
       "289  10.663966   5.655992   6.154858   7.235619          3.465736   \n",
       "343   7.431892   8.848509  10.177932   7.283448          9.646593   \n",
       "\n",
       "     Delicatessen  \n",
       "66       3.295837  \n",
       "109      1.098612  \n",
       "128      1.098612  \n",
       "137      3.583519  \n",
       "142      1.098612  \n",
       "154      2.079442  \n",
       "183     10.777768  \n",
       "184      2.397895  \n",
       "187      1.098612  \n",
       "203      2.890372  \n",
       "233      1.945910  \n",
       "285      2.890372  \n",
       "289      3.091042  \n",
       "343      3.610918  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 对于每一个特征，找到值异常高或者是异常低的数据点\n",
    "for feature in log_data.keys():\n",
    "    \n",
    "    # TODO：计算给定特征的Q1（数据的25th分位点）\n",
    "    Q1 = np.percentile(log_data[feature], 25)\n",
    "    \n",
    "    # TODO：计算给定特征的Q3（数据的75th分位点）\n",
    "    Q3 = np.percentile(log_data[feature], 75)\n",
    "    \n",
    "    # TODO：使用四分位范围计算异常阶（1.5倍的四分位距）\n",
    "    step = 1.5 * (Q3 - Q1)\n",
    "    \n",
    "    # 显示异常点\n",
    "    print \"Data points considered outliers for the feature '{}':\".format(feature)\n",
    "    display(log_data[~((log_data[feature] >= Q1 - step) & (log_data[feature] <= Q3 + step))])\n",
    "    \n",
    "# 可选：选择你希望移除的数据点的索引\n",
    "outliers  = [65, 66, 75, 128, 154]\n",
    "\n",
    "# 如果选择了的话，移除异常点\n",
    "good_data = log_data.drop(log_data.index[outliers]).reset_index(drop = True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 问题 4\n",
    "*请列出所有在多于一个特征下被看作是异常的数据点。这些点应该被从数据集中移除吗？为什么？把你认为需要移除的数据点全部加入到到`outliers`变量中。* "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**回答:**\n",
    "\n",
    "65, 66, 75, 128, 154.\n",
    "\n",
    "\n",
    "应该被移除。如果一个特征因为过高在区间外，很可是专门购置一种商品的大客户，不能忽略。如果一个特征因为过低在区间外，说明这个客户不需要这种商品，也是正常现象。但是如果两个特征都在区间外，就很可能是其他原因引起的，比如数据采集、记录中产生的错误。并且最终只去除了 5 个数据点，并没有过多影响原数据集，所以我认为需要移除。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 特征转换\n",
    "在这个部分中你将使用主成分分析（PCA）来分析批发商客户数据的内在结构。由于使用PCA在一个数据集上会计算出最大化方差的维度，我们将找出哪一个特征组合能够最好的描绘客户。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 练习: 主成分分析（PCA）\n",
    "\n",
    "既然数据被缩放到一个更加正态分布的范围中并且我们也移除了需要移除的异常点，我们现在就能够在`good_data`上使用PCA算法以发现数据的哪一个维度能够最大化特征的方差。除了找到这些维度，PCA也将报告每一个维度的*解释方差比（explained variance ratio）*--这个数据有多少方差能够用这个单独的维度来解释。注意PCA的一个组成部分（维度）能够被看做这个空间中的一个新的“特征”，但是它是原来数据中的特征构成的。\n",
    "\n",
    "在下面的代码单元中，你将要实现下面的功能：\n",
    " - 导入`sklearn.decomposition.PCA`并且将`good_data`用PCA并且使用6个维度进行拟合后的结果保存到`pca`中。\n",
    " - 使用`pca.transform`将`log_samples`进行转换，并将结果存储到`pca_samples`中。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f5e43fa8a10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# TODO：通过在good_data上使用PCA，将其转换成和当前特征数一样多的维度\n",
    "from sklearn.decomposition import PCA\n",
    "pca = PCA(6)\n",
    "pca.fit(good_data)\n",
    "\n",
    "# TODO：使用上面的PCA拟合将变换施加在log_samples上\n",
    "pca_samples = pca.transform(log_samples)\n",
    "\n",
    "# 生成PCA的结果图\n",
    "pca_results = vs.pca_results(good_data, pca)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 问题 5\n",
    "*数据的第一个和第二个主成分* **总共** *表示了多少的方差？*  前四个主成分呢？使用上面提供的可视化图像，讨论从用户花费的角度来看前四个**主要成分**的消费行为最能代表哪种类型的客户并给出你做出判断的理由。\n",
    "\n",
    "**提示：** 某一特定维度上的正向增长对应**正权**特征的**增长**和**负权**特征的**减少**。增长和减少的速率和每个特征的权重相关。[参考资料(英文)](https://onlinecourses.science.psu.edu/stat505/node/54)。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**回答:**\n",
    "\n",
    "第一个和第二个主成分总共表示了 0.7068 的方差。前四个主成分总共表示了 0.9311 的方差。\n",
    "\n",
    "第一个主要成分主要随着Milk、Grocery和Detergents_Paper的下降而增长，其中最主要的是Detergents_Paper，说明餐巾纸的用量可以很大程度上影响Milk和Grocery，因此代表了咖啡店的消费行为，人流量越大，餐巾纸用量越大，购买的咖啡和小食也相应增多。\n",
    "\n",
    "第二个主要成分主要随着Fresh、Frozen和Delicatessen的下降而增长，而且三者的差距不大，考虑到三者都是正餐常用的食材，因此代表了饭店的消费行为，各种食材大量购进。\n",
    "\n",
    "第三个主要成分主要随着Fresh的下降和Delicatessen的上升而增长，说明Fresh和Delicatessen此消彼长，代表了主要售卖Fresh或Delicatessen其中一种的客户。\n",
    "\n",
    "第四个主要成分主要随着Frozen的上升和Delicatessen的下降而增长，说明Frozen和Delicatessen此消彼长，代表了主要售卖Frozen或Delicatessen其中一种的客户。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 观察\n",
    "运行下面的代码，查看经过对数转换的样本数据在进行一个6个维度的主成分分析（PCA）之后会如何改变。观察样本数据的前四个维度的数值。考虑这和你初始对样本点的解释是否一致。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
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       "\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Dimension 1</th>\n",
       "      <th>Dimension 2</th>\n",
       "      <th>Dimension 3</th>\n",
       "      <th>Dimension 4</th>\n",
       "      <th>Dimension 5</th>\n",
       "      <th>Dimension 6</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1.3241</td>\n",
       "      <td>-1.9242</td>\n",
       "      <td>-0.2657</td>\n",
       "      <td>0.0144</td>\n",
       "      <td>-0.5492</td>\n",
       "      <td>0.2026</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>-0.3548</td>\n",
       "      <td>1.3830</td>\n",
       "      <td>0.1156</td>\n",
       "      <td>0.6725</td>\n",
       "      <td>0.3236</td>\n",
       "      <td>-0.8801</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>-2.0483</td>\n",
       "      <td>-0.7480</td>\n",
       "      <td>0.9237</td>\n",
       "      <td>1.2860</td>\n",
       "      <td>-0.0332</td>\n",
       "      <td>0.0786</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Dimension 1  Dimension 2  Dimension 3  Dimension 4  Dimension 5  \\\n",
       "0       1.3241      -1.9242      -0.2657       0.0144      -0.5492   \n",
       "1      -0.3548       1.3830       0.1156       0.6725       0.3236   \n",
       "2      -2.0483      -0.7480       0.9237       1.2860      -0.0332   \n",
       "\n",
       "   Dimension 6  \n",
       "0       0.2026  \n",
       "1      -0.8801  \n",
       "2       0.0786  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 展示经过PCA转换的sample log-data\n",
    "display(pd.DataFrame(np.round(pca_samples, 4), columns = pca_results.index.values))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 练习：降维\n",
    "当使用主成分分析的时候，一个主要的目的是减少数据的维度，这实际上降低了问题的复杂度。当然降维也是需要一定代价的：更少的维度能够表示的数据中的总方差更少。因为这个，*累计解释方差比（cumulative explained variance ratio）*对于我们确定这个问题需要多少维度非常重要。另外，如果大部分的方差都能够通过两个或者是三个维度进行表示的话，降维之后的数据能够被可视化。\n",
    "\n",
    "在下面的代码单元中，你将实现下面的功能：\n",
    " - 将`good_data`用两个维度的PCA进行拟合，并将结果存储到`pca`中去。\n",
    " - 使用`pca.transform`将`good_data`进行转换，并将结果存储在`reduced_data`中。\n",
    " - 使用`pca.transform`将`log_samples`进行转换，并将结果存储在`pca_samples`中。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# TODO：通过在good data上进行PCA，将其转换成两个维度\n",
    "pca = PCA(2)\n",
    "pca.fit(good_data)\n",
    "\n",
    "# TODO：使用上面训练的PCA将good data进行转换\n",
    "reduced_data = pca.transform(good_data)\n",
    "\n",
    "# TODO：使用上面训练的PCA将log_samples进行转换\n",
    "pca_samples = pca.transform(log_samples)\n",
    "\n",
    "# 为降维后的数据创建一个DataFrame\n",
    "reduced_data = pd.DataFrame(reduced_data, columns = ['Dimension 1', 'Dimension 2'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 观察\n",
    "运行以下代码观察当仅仅使用两个维度进行PCA转换后，这个对数样本数据将怎样变化。观察这里的结果与一个使用六个维度的PCA转换相比较时，前两维的数值是保持不变的。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Dimension 1</th>\n",
       "      <th>Dimension 2</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1.3241</td>\n",
       "      <td>-1.9242</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>-0.3548</td>\n",
       "      <td>1.3830</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>-2.0483</td>\n",
       "      <td>-0.7480</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Dimension 1  Dimension 2\n",
       "0       1.3241      -1.9242\n",
       "1      -0.3548       1.3830\n",
       "2      -2.0483      -0.7480"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 展示经过两个维度的PCA转换之后的样本log-data\n",
    "display(pd.DataFrame(np.round(pca_samples, 4), columns = ['Dimension 1', 'Dimension 2']))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 可视化一个双标图（Biplot）\n",
    "双标图是一个散点图，每个数据点的位置由它所在主成分的分数确定。坐标系是主成分（这里是`Dimension 1` 和 `Dimension 2`）。此外，双标图还展示出初始特征在主成分上的投影。一个双标图可以帮助我们理解降维后的数据，发现主成分和初始特征之间的关系。\n",
    "\n",
    "运行下面的代码来创建一个降维后数据的双标图。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7f5e43a625d0>"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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b6Bxo4HUttJnkTuj5ZJusfh06CMrfQufO2wYdsdPPJ6DZ8w9Cp5vYA+A7AK4zU6czKMeT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YhImJ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\nAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f5e435ecb50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Create a biplot\n",
    "vs.biplot(good_data, reduced_data, pca)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 观察\n",
    "\n",
    "一旦我们有了原始特征的投影（红色箭头），就能更加容易的理解散点图每个数据点的相对位置。\n",
    "\n",
    "在这个双标图中，哪些初始特征与第一个主成分有强关联？哪些初始特征与第二个主成分相关联？你观察到的是否与之前得到的 pca_results 图相符？"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 聚类\n",
    "\n",
    "在这个部分，你讲选择使用K-Means聚类算法或者是高斯混合模型聚类算法以发现数据中隐藏的客户分类。然后，你将从簇中恢复一些特定的关键数据点，通过将它们转换回原始的维度和规模，从而理解他们的含义。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 问题 6\n",
    "*使用K-Means聚类算法的优点是什么？使用高斯混合模型聚类算法的优点是什么？基于你现在对客户数据的观察结果，你选用了这两个算法中的哪一个，为什么？*"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**回答:**\n",
    "\n",
    "K_Means聚类算法优点是原理简单，易于理解，计算量小，可以快速地收敛，参数简单，只有一个k。\n",
    "\n",
    "高斯混合模型聚类算法的优点是软聚类，可以给出点在每个聚类中的可能性，对于后续处理可以提供更多信息。\n",
    "\n",
    "我选用了高斯混合模型聚类算法。降维到二维后，可以看到数据的聚集，而且没有明显的分割线，因此软聚类更加适合，所以选择高斯混合模型聚类算法。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 练习: 创建聚类\n",
    "\n",
    "针对不同情况，有些问题你需要的聚类数目可能是已知的。但是在聚类数目不作为一个**先验**知道的情况下，我们并不能够保证某个聚类的数目对这个数据是最优的，因为我们对于数据的结构（如果存在的话）是不清楚的。但是，我们可以通过计算每一个簇中点的**轮廓系数**来衡量聚类的质量。数据点的[轮廓系数](http://scikit-learn.org/stable/modules/generated/sklearn.metrics.silhouette_score.html)衡量了它与分配给他的簇的相似度，这个值范围在-1（不相似）到1（相似）。**平均**轮廓系数为我们提供了一种简单地度量聚类质量的方法。\n",
    "\n",
    "在接下来的代码单元中，你将实现下列功能：\n",
    " - 在`reduced_data`上使用一个聚类算法，并将结果赋值到`clusterer`，需要设置 `random_state` 使得结果可以复现。\n",
    " - 使用`clusterer.predict`预测`reduced_data`中的每一个点的簇，并将结果赋值到`preds`。\n",
    " - 使用算法的某个属性值找到聚类中心，并将它们赋值到`centers`。\n",
    " - 预测`pca_samples`中的每一个样本点的类别并将结果赋值到`sample_preds`。\n",
    " - 导入sklearn.metrics.silhouette_score包并计算`reduced_data`相对于`preds`的轮廓系数。\n",
    "   - 将轮廓系数赋值给`score`并输出结果。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.421916846463\n"
     ]
    }
   ],
   "source": [
    "# TODO：在降维后的数据上使用你选择的聚类算法\n",
    "from sklearn.mixture import GaussianMixture\n",
    "clusterer = GaussianMixture(n_components = 2, random_state = 15)\n",
    "clusterer.fit(reduced_data)\n",
    "\n",
    "# TODO：预测每一个点的簇\n",
    "preds = clusterer.predict(reduced_data)\n",
    "\n",
    "# TODO：找到聚类中心\n",
    "centers = clusterer.means_\n",
    "\n",
    "# TODO：预测在每一个转换后的样本点的类\n",
    "sample_preds = clusterer.predict(pca_samples)\n",
    "\n",
    "# TODO：计算选择的类别的平均轮廓系数（mean silhouette coefficient）\n",
    "from sklearn.metrics import silhouette_score\n",
    "score = silhouette_score(reduced_data, preds)\n",
    "print score"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 问题 7\n",
    "\n",
    "*汇报你尝试的不同的聚类数对应的轮廓系数。在这些当中哪一个聚类的数目能够得到最佳的轮廓系数？* \n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**回答:**\n",
    "\n",
    "| 聚类数 | 轮廓系数 |\n",
    "|:------:|:--------:|\n",
    "| 2      | 0.421916846463 |\n",
    "| 3      | 0.37781736387  |\n",
    "| 4      | 0.330138622592 |\n",
    "| 5      | 0.262587197001 |\n",
    "| 6      | 0.32887943115  |\n",
    "| 7      | 0.338629896879 |\n",
    "| 8      | 0.301354280629 |\n",
    "\n",
    "聚类数为2时，能够得到最佳的轮廓系数"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 聚类可视化\n",
    "一旦你选好了通过上面的评价函数得到的算法的最佳聚类数目，你就能够通过使用下面的代码块可视化来得到的结果。作为实验，你可以试着调整你的聚类算法的聚类的数量来看一下不同的可视化结果。但是你提供的最终的可视化图像必须和你选择的最优聚类数目一致。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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bUpUGDhzIvvvuS0NDQ0HfVyAkIiIiIhKDtWvXMmTIEEaPHo2Zxd2cquKc49VX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\nLyLl2f6ZAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f5e4434ee90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 从已有的实现中展示聚类的结果\n",
    "vs.cluster_results(reduced_data, preds, centers, pca_samples)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 练习: 数据恢复\n",
    "上面的可视化图像中提供的每一个聚类都有一个中心点。这些中心（或者叫平均点）并不是数据中真实存在的点，但是是所有预测在这个簇中的数据点的*平均*。对于创建客户分类的问题，一个簇的中心对应于*那个分类的平均用户*。因为这个数据现在进行了降维并缩放到一定的范围，我们可以通过施加一个反向的转换恢复这个点所代表的用户的花费。\n",
    "\n",
    "在下面的代码单元中，你将实现下列的功能：\n",
    " - 使用`pca.inverse_transform`将`centers` 反向转换，并将结果存储在`log_centers`中。\n",
    " - 使用`np.log`的反函数`np.exp`反向转换`log_centers`并将结果存储到`true_centers`中。\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Fresh</th>\n",
       "      <th>Milk</th>\n",
       "      <th>Grocery</th>\n",
       "      <th>Frozen</th>\n",
       "      <th>Detergents_Paper</th>\n",
       "      <th>Delicatessen</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Segment 0</th>\n",
       "      <td>8953.0</td>\n",
       "      <td>2114.0</td>\n",
       "      <td>2765.0</td>\n",
       "      <td>2075.0</td>\n",
       "      <td>353.0</td>\n",
       "      <td>732.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Segment 1</th>\n",
       "      <td>3552.0</td>\n",
       "      <td>7837.0</td>\n",
       "      <td>12219.0</td>\n",
       "      <td>870.0</td>\n",
       "      <td>4696.0</td>\n",
       "      <td>962.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            Fresh    Milk  Grocery  Frozen  Detergents_Paper  Delicatessen\n",
       "Segment 0  8953.0  2114.0   2765.0  2075.0             353.0         732.0\n",
       "Segment 1  3552.0  7837.0  12219.0   870.0            4696.0         962.0"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# TODO：反向转换中心点\n",
    "log_centers = pca.inverse_transform(centers)\n",
    "\n",
    "# TODO：对中心点做指数转换\n",
    "true_centers = np.exp(log_centers)\n",
    "\n",
    "# 显示真实的中心点\n",
    "segments = ['Segment {}'.format(i) for i in range(0,len(centers))]\n",
    "true_centers = pd.DataFrame(np.round(true_centers), columns = data.keys())\n",
    "true_centers.index = segments\n",
    "display(true_centers)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 问题 8\n",
    "考虑上面的代表性数据点在每一个产品类型的花费总数，*你认为这些客户分类代表了哪类客户？为什么？*需要参考在项目最开始得到的统计值来给出理由。\n",
    "\n",
    "**提示：** 一个被分到`'Cluster X'`的客户最好被用 `'Segment X'`中的特征集来标识的企业类型表示。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**回答:**\n",
    "\n",
    "Segment 0 代表了饭店。Fresh和Frozen都在中位数以上，说明食材的需求量很大，因此应该是饭店。\n",
    "\n",
    "Segment 1 代表了超市。Milk、Grocery和Detergents_Paper都超过了75%分位点，Delicatessen也超过了中位数，说明各种商品的需求量都很大，因此应该是超市。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 问题 9\n",
    "*对于每一个样本点 * **问题 8**  *中的哪一个分类能够最好的表示它？你之前对样本的预测和现在的结果相符吗？*\n",
    "\n",
    "运行下面的代码单元以找到每一个样本点被预测到哪一个簇中去。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Sample point 0 predicted to be in Cluster 0\n",
      "Sample point 1 predicted to be in Cluster 0\n",
      "Sample point 2 predicted to be in Cluster 1\n"
     ]
    }
   ],
   "source": [
    "# 显示预测结果\n",
    "for i, pred in enumerate(sample_preds):\n",
    "    print \"Sample point\", i, \"predicted to be in Cluster\", pred"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**回答:**\n",
    "\n",
    "样本点0应该被分到 Cluster 0 中，即为饭店。\n",
    "\n",
    "样本点1在两个 Cluster 的边界，都有可能。\n",
    "\n",
    "样本点2应该被分到 Cluster 1 中，即为超市。\n",
    "\n",
    "我之前对样本的预测是样本点0为饭店，样本点1为咖啡店，样本点2为超市，与现在的结果，样本点01为饭店，样本点2为超市，基本相符。\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 结论\n",
    "\n",
    "在最后一部分中，你要学习如何使用已经被分类的数据。首先，你要考虑不同组的客户**客户分类**，针对不同的派送策略受到的影响会有什么不同。其次，你要考虑到，每一个客户都被打上了标签（客户属于哪一个分类）可以给客户数据提供一个多一个特征。最后，你会把客户分类与一个数据中的隐藏变量做比较，看一下这个分类是否辨识了特定的关系。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "### 问题 10\n",
    "在对他们的服务或者是产品做细微的改变的时候，公司经常会使用[A/B tests](https://en.wikipedia.org/wiki/A/B_testing)以确定这些改变会对客户产生积极作用还是消极作用。这个批发商希望考虑将他的派送服务从每周5天变为每周3天，但是他只会对他客户当中对此有积极反馈的客户采用。*这个批发商应该如何利用客户分类来知道哪些客户对它的这个派送策略的改变有积极的反馈，如果有的话？你需要给出在这个情形下A/B 测试具体的实现方法，以及最终得出结论的依据是什么？*  \n",
    "**提示：** 我们能假设这个改变对所有的客户影响都一致吗？我们怎样才能够确定它对于哪个类型的客户影响最大？"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**回答：**\n",
    "\n",
    "派送服务的更改对于不同类型的客户效果是不同的。比如对于饭店，每天流水都很大，频繁派送可以保证食材的新鲜。\n",
    "\n",
    "为了确定派送服务的更改产生的效果，可以根据聚类的结果，将客户分成两类。在每类用户中，一半改变派送服务，一半保持原样。一段时间后，看整体上改变派送服务客户的需求量如何变化。如果需求量上升了，就说明有积极的作用；如果需求量下降了，说明产生了消极作用。\n",
    "\n",
    "最终，根据每类客户产生的作用积极还是消极，决定以后对这类用户是更改还是保持派送服务。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 问题 11\n",
    "通过聚类技术，我们能够将原有的没有标记的数据集中的附加结构分析出来。因为每一个客户都有一个最佳的划分（取决于你选择使用的聚类算法），我们可以把*用户分类*作为数据的一个[**工程特征**](https://en.wikipedia.org/wiki/Feature_learning#Unsupervised_feature_learning)。假设批发商最近迎来十位新顾客，并且他已经为每位顾客每个产品类别年度采购额进行了预估。进行了这些估算之后，批发商该如何运用它的预估和**非监督学习的结果**来对这十个新的客户进行更好的预测？\n",
    "\n",
    "**提示：**在下面的代码单元中，我们提供了一个已经做好聚类的数据（聚类结果为数据中的cluster属性），我们将在这个数据集上做一个小实验。尝试运行下面的代码看看我们尝试预测‘Region’的时候，如果存在聚类特征'cluster'与不存在相比对最终的得分会有什么影响？这对你有什么启发？"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "使用cluster特征的得分 0.666666666667\n",
      "不使用cluster特征的得分 0.64367816092\n"
     ]
    }
   ],
   "source": [
    "from sklearn.ensemble import RandomForestClassifier\n",
    "from sklearn.model_selection import train_test_split\n",
    "\n",
    "# 读取包含聚类结果的数据\n",
    "cluster_data = pd.read_csv(\"cluster.csv\")\n",
    "y = cluster_data['Region']\n",
    "X = cluster_data.drop(['Region'], axis = 1)\n",
    "\n",
    "# 划分训练集测试集\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=24)\n",
    "\n",
    "clf = RandomForestClassifier(random_state=24)\n",
    "clf.fit(X_train, y_train)\n",
    "print \"使用cluster特征的得分\", clf.score(X_test, y_test)\n",
    "\n",
    "# 移除cluster特征\n",
    "X_train = X_train.copy()\n",
    "X_train.drop(['cluster'], axis=1, inplace=True)\n",
    "X_test = X_test.copy()\n",
    "X_test.drop(['cluster'], axis=1, inplace=True)\n",
    "clf.fit(X_train, y_train)\n",
    "print \"不使用cluster特征的得分\", clf.score(X_test, y_test)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**回答：**\n",
    "\n",
    "使用cluster特征的得分会高于不使用cluster特征的得分，这就意味着，加入cluster特征可以更好的划分客户，预测客户的其他行为。\n",
    "\n",
    "因此，通过使用cluster特征，可以预测客户的其他特征，比如地区，比如需求量的增长。咖啡店的需求量可能一直缓慢增长，饭店的需求量可能长期高速增长。这样可以预先做好货物储备，保证供应量。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 可视化内在的分布\n",
    "\n",
    "在这个项目的开始，我们讨论了从数据集中移除`'Channel'`和`'Region'`特征，这样在分析过程中我们就会着重分析用户产品类别。通过重新引入`Channel`这个特征到数据集中，并施加和原来数据集同样的PCA变换的时候我们将能够发现数据集产生一个有趣的结构。\n",
    "\n",
    "运行下面的代码单元以查看哪一个数据点在降维的空间中被标记为`'HoReCa'` (旅馆/餐馆/咖啡厅)或者`'Retail'`。另外，你将发现样本点在图中被圈了出来，用以显示他们的标签。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
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en0RERMIhyECoK3AycLdzbhDwMXBD7EZm9i0zW2BmC9atW1foNoqIhE9IKygV\npUh2bfI0mL/E+zngQgVDIiJlIMhAaBWwyjnX4D9+Ai8wasc5d69zrtY5V9urV6+CNlBEJJQCqKBU\nspRdExEpW4EFQs65NUCTmUWKpQ8HXg+qPSIiRSOACkolS9k1EZGyFfQ6QmOBqWa2GBgI/Czg9oiI\nhF9VH68wQv0oLwtUP0qFEjKl7JqISNkKNBByzjX6w95qnHNfcs59FGR7RESKRlUfmPRDaHjM+6kg\nKDPKromUrS5dujBw4ED69+/PBRdcwIYNCVdwAWDDhg3cddddaR37tNNOA2DlypX0798/67ZKfgSd\nERIREQmOsmsiZWvvvfemsbGRpUuXcsABB3DnnXcm3b4zgdArr7ySUZt27NiReiPJGQVCIiJS3pRd\nEwm9JjYxltnUMZWxzKaJTTk9/qmnnsrq1avbHt9+++0MHjyYmpoafvzjHwNwww03sGLFCgYOHMi4\nceNoaWlh+PDhnHzyyVRXV/PUU0+17d+tW7cO59i5cyfjxo1rO+7kyZMBmDNnDsOGDWPkyJGceOKJ\nOe2XJNc19SYiIiIiIsFoYhMDeIgWWmllF42sZSrLWMTlVNEj6+Pv3LmT2bNnM2aMNyR21qxZLF++\nnHnz5uGcY+TIkcydO5fbbruNpUuX0tjYCHjZm+nTp9OjRw8++OADTjnlFEaOHImZxT3PlClT6Nmz\nJ/Pnz2f79u0MHTqUs846C4BXX32VpUuX0q9fv6z7I+lTICQSQk1sYgLzaWANQ+jNeAbn5Je9iIhI\nsZnA/LYgCKCVXbTQygTmM4nhGR9369atDBw4kNWrV3PCCSfwhS98AfACoVmzZjFo0CAAWlpaWL58\nOYcffni7/Z1z3HjjjcydO5eKigpWr17N+++/T+/eveOeb9asWSxevJgnnngCgI0bN7J8+XL22GMP\n6urqFAQFQIGQSMjk+5svERGRYtLAmrYgKKKVXcxjTVbHjcwR2rJlCyNGjODOO+/kmmuuwTnHD37w\nA+rr69ttv3LlynaPp06dyrp161i4cCGVlZX07duXbdu2JTyfc45JkyYxYsSIds/PmTOHfffdN6u+\nSGY0R0gkZJJ985Ur+R5rLSIikitD6E1lzC1rJRXUET/z0ln77LMPd9xxB7/85S/ZsWMHI0aM4P77\n76elpQWA1atXs3btWrp3787mzZvb9tu4cSMHH3wwlZWVvPDCC7zzzjtJzzNixAjuvvtuWltbAXjz\nzTf5+OOPc9IHyYwyQiIhk69vviKUcRIRkWIynsFMZVnb/1uVVNCNSsYzOGfnGDRoEDU1Nfz+97/n\nsssuY9myZZx66qmAV/jgkUdkSYmcAAAgAElEQVQe4aijjmLo0KH079+fc845h+uvv54LLriA6upq\namtrOf7445Oe46qrrmLlypWcfPLJOOfo1asXTz75ZM76IJ1nzrmg25C22tpat2DBgqCbIZJXY5nN\nZBa3C4YqqaCemqzGQhfq+CIiIqksW7aME044Ie3tI3Nn57GGOs2dlSjxPktmttA5V5tqX2WEREIm\n39985TvjJCIikmtV9NCXdZJzmiMkEjJV9GARl1NPDXX0pp6anA5by/dYaxEREZFioIyQSAjl85uv\nQoy1FhEREQk7BUIiZSaScdJYaxERCZJzLuHioyLpyLbWgQIhkTKksdYiIhKkvfbai/Xr13PggQcq\nGJKMOOdYv349e+21V8bHUCAkIiIiIgV12GGHsWrVKtatWxd0U6SI7bXXXhx22GEZ769ASEQ6p6kZ\nJkyBhiUwpBrGj4GqPkG3SkREikhlZSX9+vULuhlS5hQIiUj6mpphwIXQsgVad0DjMpg6AxZNVzAk\nIiIiRUXls0UkfROm7A6CwPvZssV7XkRERKSIKBASkfQ1LNkdBEW07oB5S4Jpj4iIiEiGFAiJSPqG\nVENlzIjayq5QVx1Me0REREQypEBIRNI3fgx022d3MFTZ1Xs8fkyw7RIRERHpJAVCIpK+qj5eYYT6\nUV4WqH6UCiWIiIhIUVLVOBHpnKo+MOmHQbdCREREJCvKCImIiIiISNlRICQiIiIiImVHgZCIiIiI\niJQdBUIiIiIiIlJ2FAiJiIiIiEjZUSAkIiIiIiJlR4GQiIiIiIiUHQVCIiIiIiJSdhQIiYiIiIhI\n2VEgJCIiIiIiZUeBkIiIiIiIlB0FQiIiIiIiUnYUCImIiEj5amqGsbdA3WjvZ1Nz0C0SkQLpGnQD\nRERERALR1AwDLoSWLdC6AxqXwdQZsGg6VPUJunUikmfKCImIiEh5mjBldxAE3s+WLd7zIlLyFAiJ\niIhIeWpYsjsIimjdAfOWBNMeESkoBUIiIiJSnoZUQ2XMLIHKrlBXHUx7RKSgFAiJiIhIeRo/Brrt\nszsYquzqPR4/Jth2iUhBKBASEREJM1U1y5+qPl5hhPpRXhaofpQKJYiUEXPOBd2GtNXW1roFCxYE\n3QwREZHCiK1qFslY6GZdRCQhM1vonKtNtZ0yQiIiImGlqmYiInmjQEhERCSsVNVMRCRvFAiJiIiE\nlaqaiYjkjQIhERGRsFJVMxGRvFEgJCIiElaqaiYikjddU28iIiJS4pqavQIEDUu84Wjjx4Qn2Kjq\nA5N+GHQrRERKjgIhEREpb7ElqhuXwdQZyryIiJQ4DY0TEZHyphLVIiJlSYGQiIiUN5WoFhEpSwqE\nRESkvKlEtYhIWVIgJCIi5U0lqkVEypICIRERKW8qUS0iUpZUNU5EREQlqkVEyo4yQiIiIiLFrqkZ\nxt4CdaO9n03NQbdIJPSUERIREREpZloLSyQjygiJiIiIFDOthSWSEQVCIiIiIsVMa2GJZESBkIiI\niEgx01pYIhlRICQiIiJSzLQWlkhGAg+EzKyLmb1mZjOCbouIiIhI0dFaWCIZCUPVuO8Cy4AeQTdE\nREREpChpLSyRTgs0I2RmhwHnAfcF2Q4RERERESkvQQ+N+x9gPLAr4HaIiIiIiEgZCSwQMrPzgbXO\nuYUptvuWmS0wswXr1q0rUOtERERERKSUBZkRGgqMNLOVwKPA583skdiNnHP3OudqnXO1vXr1KnQb\nRUSkHDQ1w9hboG6097OpOegWiYhInplzLug2YGZnAN93zp2fbLva2lq3YMGCwjRKRETKQ1MzDLgQ\nWrZ4i1BGSg+r6paISFEys4XOudpU2wU9R0hEpKQ0sYmxzKaOqYxlNk1sCrpJksqEKbuDIPB+tmzx\nnhcRkZIVhvLZOOfmAHMCboaISFaa2MQAHqKFVlrZRSNrmcoyFnE5VVohILwaluwOgiJad8C8JcG0\nR0RECkIZIRGRHJnA/LYgCKCVXbTQygTmB9wySWpItTccLlplV29hShERKVkKhEREcqSBNW1BUEQr\nu5jHmoBaJGkZP8abExQJhiJzhMaPCbZdIiKSVwqERERyZAi9qYz5tVpJBXX0DqhFkpaqPl5hhPpR\nXhaofpQKJUjpUWVEkQ5CUTUuXaoaJyJhFjtHqJIKulGpOUJBa2r2Ch80LPGGwY0foyBHyosqI0qZ\nUdU4EZECq6IHi7icemqoozf11CgIClrkBnDyNJi/xPs54EJ9Gy7lRZURReIKRdU4kWLWxCYmMJ8G\n1jCE3oxnsG58y1gVPZjE8KCbIRHJbgAn/TDYtokUiiojisSlQEgkCyqXLBJyhboB1PA7CbMh1dC4\nrP2/BVVGFNHQOJFsqFyySMgVojS2ht9J2KkyokhcCoREsqByySIhV4gbQM2/kLBTZUSRuDQ0TiQL\nQ+hNI2vbBUMqlywSIpEbwAlTvOFwdXkYtqb5F1IMqvpoXpxIDAVCIlkYz2CmsqxDueTxDA66aSIS\nke8bQM2/EBEpShoaJ5IFlUsWEc2/EBEpTsoIiWRJ5ZJFylwhht+JiEjOKRASERHJluZfiIgUHQ2N\nExERERGRsqNASEREREREyo4CIRERERERKTsKhEREREREpOwoEBIRERERkbKjQEhKQhObGMts6pjK\nWGbTxKagmyQiIiIiIaby2VL0mtjEAB6ihVZa2UUja5nKMi1sKiIiIiIJKSMkRW8C89uCIIBWdtFC\nKxOYH3DLRERERCSsFAhJ0WtgTVsQFNHKLuaxJqAWiYiIiEjYKRCSojeE3lTGfJQrqaCO3gG1SERE\nRETCToGQFL3xDKYblW3BUCUVdKOS8QwOuGUiIiIiElYqliBFr4oeLOJyJjCfeayhjt6MZ7AKJYiI\niIhIQgqEpCRU0YNJDA+6GSIiIiJSJDQ0TkREREREyo4CIREREcm/pmYYewvUjfZ+NjUH3SIRKXMa\nGiciIiLpa2qGCVOgYQkMqYbxY6CqT+p9BlwILVugdQc0LoOpM2DR9NT7iojkiTJCIiIikp5IQDN5\nGsxf4v0ccGHq7M6EKbuDIPB+tmzxnhcRCYgCIZEy1cQmxjKbOqYyltk0sSnoJolI2GUa0DQs2b1P\nROsOmLckP+0UEUmDhsaJlKEmNjGAh2ihlVZ20chaprKMRVyusuMiklimAc2Qam84XPS+lV2hrjr3\nbRQRSZMyQiJ5EuaMywTmtwVBAK3sooVWJjA/4JaJSKgNqfYCmGjpBDTjx0C3fXbvW9nVezx+TH7a\nKSKSBgVCUvbyEbBEMi6TWcx81jCZxQzgodAEQw2saQuCIlrZxTzWBNQiESkKmQY0VX28wgj1o7yg\nqX6UCiWISOA0NE7KWr6GiCXLuIRh4dch9KaRte2CoUoqqKN3gK0SkdCLBDQTpnjD4erSrBoX2XfS\nD/PfRhGRNCkQkrKWr4Al7BmX8QxmKsva+l5JBd2oZDyDg26aiISdAhoRKREaGidlLV8ByxB6Uxnz\nzytMGZcqerCIy6mnhjp6U0+NCiWIiIhIWVFGSMparoeINbGJCcxnLqupwOiKsQMXyoxLFT1CMUxP\nREREJAgKhKSs5XKIWOx8o64YXTBO4iCGcSjjGZy/jEsmK72LiIiIlDEFQlLWIkPEJjCfeayhjt4Z\nByyx84124DCMYRya38xLZKX3yCKHjctg6gxVZBIRiUdfHImIT4GQlL1cDRErVIGEyPC7BtYwhN6M\nv/fvVCVa6V0TmkVEdtMXRyISRcUSRHKkEAUS4q5PNK4rTYfs2X7DdFZ6FxEpNxOm7A6CoP0XR4XU\n1Axjb4G60d7PpubCnl9EAAVCIjkznsF0o7ItGMpHgYS45b736cKEGwa03zCdld5FRMpNw5LdQVBE\nob84imSlJk+D+Uu8nwMuVDAkEgAFQiI5UoiS1HGH33U15p1ycPorveubSBEpV0Oqd/+ujCj0F0dh\nyUqJiOYIieRStvONOsz/iSnckLDc97GnQv0+qVd61/h4ESln48d4v/MivwNTfXGUD2HISokIoEBI\nJKVUwUkuzxNdfruRtUxlWbusUsJy391Ph0kXpD5Jsm8iVVghGKpgJVI4VX28L34mTEn9xVG+DKn2\nvoSKDoY0nFkkEOacC7oNaautrXULFiwIuhlSRmKDk0jgkeshbwBjmc1kFnfI9tRT0y7LFAnMYst9\npxWw1Y32xqTHqquGhsdy2h9JQ2yGLvLttDJ0IqVL/+5F8s7MFjrnalNtpzlCIknELU5AKxOYn/Nz\npVt+OzL8roFLmcTwtiCoQzU5HqKJTe1PEobx8bKb5gqIlJ9IVqp+lPe7t36UgiCRgGhonEgShVob\nCJLM/0mj/HaygK3dnKUwjI+X3TRXQKQ8VfXRcGSREFBGSCSJQqwNFJFN+e20AzZ9ExkuytCJiIgE\nRhkhkSQSFifI4dpAEZHy2/Hm/6TSqWySvokMD2Xowk/FLERESpaKJYgk0cQmbuJlZvI2YJxDX37K\n0LxUjctGLos6FKpKnvgiN9qFrmClG/zUNKldRKQopVssQYGQSAKFrBiXC4mqyXX2GMXUZ8mQbvDT\nM/YWmDytY5nj+lHKqoqIhJiqxolkqZAV43IhXjW5ziqKPjc1ezeodaO9n03NQbeo+BR7tbpCfQZU\nzEJEpKRpjpBIAoWsGJdMIYeqhaXPCcVmMhqXeXNslMnonGK+wS/kZ0ALX4qIlDRlhEQSKGTFuETS\nXh8oR8LQ56SKPZORQBObGMts6pjKWGbn7f1tU8zV6gr5GRg/xhsyGLlWKmYhIlJSFAiJJJBNOetc\nKfRQtTD0OalizmQkUOhgFwjHDX6mw9uSfQZyPWRO5eZFREqahsaJJJBNOetcKfRQtTD0OakSHKqU\n9mK4uRS5wQ+iWh1kN7wt0WfghCPzM2RO5eZFREqWAiEJjTCWbY4UIMilzvSzU+sD5Ug++pwzJbju\nTmDzsoK8wU82vC1VmxJ9BiDzY4qISFnS0DgJhUCGBwWgs/0M/VC1QivBoUqhn5eVD9kOcRz5Odi/\nBxx8IFxynvcZeP2tkhs2KSIi+RVYIGRmVWb2gpm9bmb/MLPvBtUWCV6Yyjbnc+J6uv2MtOErPMNI\njuISjqeO3tRTozV9IpmMhse8n0UcBEGZBruZFmuIDKn73bOw9kP4aCM8/UJ2xxQRkbIV5NC4HcD3\nnHOvmll3YKGZ/ck593qAbZKAhKVsc+yCoo2sZSrLchZ8pNPPeG3QoqalK/TzsvIh0yGOyYbUleCw\nyYSamr0+NyzxAsBCzu8SESkhgWWEnHPNzrlX/b9vBpYBhwbVHglWWIYH5TszlU4/w5QdK7gyXSw1\nF4vhFpVMhzgmG1JXgsMm44pkxSZPg/lLvJ8DLiybfysiIrkUimIJZtYXGAQ0BNsSCcp4BjOVZW0B\nQFDDg/KdmUqnn2HJjhWcFkstL5kUa0hVNbAcKrxlU2hCRETaCbxYgpl1A/4AXOuc6zAZw8y+ZWYL\nzGzBunXrCt9AKYjI8KB6agKdC5PvzFQ6/QxLdiyVnM+lKtHFUktCWDJ1YVj/KGgluJaWiEhQzDkX\n3MnNKoEZwPPOuV+l2r62ttYtWLAg/w2TshU7PyeSsSlkUBaGNsRv2O55CU0jahjwk+60VOzMXRvr\nRntDfTo8X+0VRpBgxGbqIsFHUJm6yOcwiPWPwmDsLd5wuNisWP0oZYRERHxmttA5V5tquyCrxhkw\nBViWThAkUghhyEyFoQ0dxMxLmND7bVp2bM/tPCZV/QqnsGXqSqxqYKcpKyYikjNBzhEaClwGLDGz\nRv+5G51z/xdgm0RCsaBoGNrQTszNcEPtQbTu0f57lKznMZVT1a9ioqFY6StENbdIUYhyzoqJiORI\nYIGQc+4lwII6v0jBFHmp2yY2MWHYRhq+di5D5q1l/IQlDJm3lsZBB9C6R5e27bKex6QbvHBKVaBA\nPIUs9lEORSFERAog0DlCnaU5QlJ0wja/opPa5ivt2EZrV6Pyk510a9nBzLOf55znR9DSfQ/v+bDM\nYwqDIg98Adi1Cz54E957Df75IvxhBizvCo17Fd1nuGA0d0dEJDTSnSMUivLZIiUri1K3TWxiAvNp\nYA1DAlpks21No65e8rZ1jy60dINHrjiGRZ/9ExNeuY553TcFsghoGK5Px0aVSAnwhntg9s1gXaH1\nYzgROOZQ2KNambpENIRQRKToKBASyacMb45iK8c1spapLCt4xiXumkZ7dGHeecdSNfKnTOoezM1w\nWK5PB6Wyxkvrx15WiO14I5gdHHU43Jrj6n2lkD2L0BBCEZGiE/g6QiLFIqN1czKshNaWicllVbYM\nJFzTqO+nA71hDcv16aBUsgInXwFXPA3Xr4QD+uXnHDGVCJk8zXsc1BpF2VI1NxGRoqNASCQNkQzE\nZBYznzVMZjEDeCh1MJThzVHcTEy2VdkyMJ7BdKOyLRiKzAUaz+CCtiNWWK5PB6VSArzbwXDEabBn\n9/ydI2xlubMVKfZRP8p7v+tHFd+QSBGRMqNASCQNGWcgMrw5SpiJyaYqWwZCuaYR4bk+HSgrkL5S\nyZ5FK/c1jkREiozmCImkIasMRAalbsczmKksawu+gszEhG5NI8J1fdpRCfD0aU6NiIgETIGQSBqG\n0JtG1rYLhrLJQKSqeBbJxExgPvNYE0hVtjAL9fXRGi/p0QK68ZVSAQkRkZDTOkIiaYitUpbNujm5\nPJbkVihLcmdg27ZtTJs2jQcffJAVK1awbds29ttvP0477TSuvvpqBg/uRObsjkHw4Vtw+Klw5XO5\nbWjkpl/ZM0+RrzsmaVCgK1IQ6a4jpEBIJE2Rm+RsMxBjmc1kFnfILtVT024IWqnclBeLUghQnXNM\nnDiRX/ziF6xfvz7hdrW1tdx1113pBUT5DISkPS3KWtoU6IoUjBZUFcmxXM2VSWe+UWjXySlhyQpi\nhG2OVDy7du3iyiuv5MEHH0y57YIFCzj99NN54oknOPfccztu8NE7MONa2NkKm97znnv/H/DA+VC5\nN3z5Xth7/xz3IM+K4Zv4UiwgIbsV0zpjxfDvRSQHVDVOpMBSVTxrYhPnMZ2P2B6+dXIylNEaTAUW\n2pLcabr++uvbBUGHH344t912G6+//jqrV69mzpw5XHHFFeyxxx4AbN26lYsuuoi4WfYPV8Dbf4WV\nL8KObd5z2zd5j/81GzYV2Vo/xbJmUamUX5f4iiXQLZZ/LyI5oEBIpMCSrc0TyQQt4YMO+xXTTXm0\njNdgKrDQluROwxtvvMHEiRPbHl955ZUsX76c66+/nhNOOIFPfepTnH766TzwwAMsWbKEvn37Al4w\ndO2113Y84MEnwoB/i//n5Mtgv6oC9SxHimXNIpVfL23FEugWy78XkRzQ0DiRHOjMfJ5kFc/GMpsW\nWuPuVyw35bGKZchZaEtyp+Huu+9u+/vnPvc57r33Xrp06RJ322OPPZaZM2dSXV3Njh07ePnll1m0\naBEDBgzYvVH33vDFO/Pd7MIplm/iVX69tBVLpcRi+fcikgMKhESylMl8nkTzjeINz4oolpvyWMUy\n5CzUJbmT2Lp1Kw888EDb4xtvvHF3EJRgnP/xxx/PRRddxKOPPgrAPffc0y6YKjlhWrMo1dwLlV8v\nXcUS6Ibp34tInqlqnEiW0q0Cl+mxAKo5iGe5MGc35YWsSJfL6yMdNTY2MmjQIAAOO+ww3nnnHSoq\nKlJWqHr++ec5++yzARg0aBCvvvpqkN3Ir4ZFcPrlsN3PtgZVrSssVcM0EV6SaWqG6i/Cpo/BOTCD\nHvvCkqf0OZGikW7VOM0REslSLjMe8eYP7c+eOQ+CCjlnJ9mcKMnehg0b2v7et29fLwiClOP8jzzy\nyLb9Nm7cWLD2FlxTM5xTDzuj/o1WGMycXPibujDMvdBEeEmXxfwUKUEKhESylMtJ9pHhWfXUUEdv\n6qnJecnsZHN28qEQfSpZTc3e2jJ1o72fcW5W99lnn7a/RwdFqcb5f/TRR3GPUTIi1672q7BxM+zY\nufu1XQ4eeabwbQrD3IswBGPR0viMSxz5vG4TpsCWbd6/E/B+btmmYglSkjRHSHIm2XCrUl4cNNeT\n7HO1XlEiQczZyXefSlLsMKrGZd5E65hhVP369aOiooJdu3axdOlS3nzzTY499tiU4/ynT5/e9vRR\nRx1VsG4VROy1ixXUxO8wzL0IQzAWkeZnPCfnKaWhgPm+bmH6jIjkmTJCkhPJhlsVS/nkTBVbxiOd\ndYzCvOZP2NuXM2l+c9+rVy/OO++8tseTJk3y/pKkFHNLSwv33Xdf2z7f+MY38tqVgou9drGCmvgd\nhvLYYSrhXIjsVLEMBexMhiff1y1Mn5GwUQaz5KhYguREsgnxgCbLh0hslbtIBmsRlwMkfC0MgV2y\ntoehfTlVN9q7cevwfDU0PNbuqeeee45zzjkHgIqKCh577DEuuuii3d+ER1Wo+uSQA7n44ovbMkJV\nVVW89dZbdO1aQgMEEl07CK5AQUSc94SqPrnLWqQ6Tq4LNmTT7k58xjM29hYv+InNwtWPCk91vs6+\nJ/m+bmEp6hE2ui5FRcUSpKCSDbcqlvLJ5SJZBqvQ84c6K+zty6lOfCt71llnMXToUAB27drFqFGj\nqK+vZ+nG9d7NXsNjtP7qep5oeJnTTjut3bC4H/3oR6UVBEH8a2cGBx/o3QAHeeMSKY/d8Jj3MxIE\n5SJrkc5xIiWc60d5n6Vsrke27S5E5qEYhnl1NsOT7+uWy89IKQnb/DrJiRL730+CMoTeNLK2Q9Yn\nMtwq2WtSeJ1ZxyhMQWvY25dTKRZfbDfvrqI3k/74IKM/cw7Lly/HOce9997Lvffey1FHHUWPHj1Y\nuXJluwIJANdddx1XXXVVEL3Lr0TXbsG07G/m8jHfJNkNVmeyFukeJ9u1iiLXYNpzsGGzV2I5k3bn\naoHRZO9JGOZlpdLZYK0QC7NqPauOiiGolk5LmBEysx5m9nMze9jMLol57a78N02KSbISySqfXDxy\nWQEvH8LevpxK8q1svHl3ww+eybSXn2PYsGHtDrNixQpee+21dkFQly5d+PnPf87EiRML3avCyNc3\n2vmab5KrG6xC3KhFX4O1H+4OgjI5Xy7ep1TvSRjmZaXS2QyPMjbB0NypkpQsI/RbYDnwB+BKM/sK\ncIlzbjtwSiEaJ8UjMtxqAvOZxxrqYirDJXstrEq50l0iua6Al2u5al/RvLcJvpVNNERwSq+3+etf\n/8qcOXO46667mD59Ojt37i4bfcghh/Ctb32Lb37zm1RVVRWsG4HIxzfaucrcxMpV1qIQ2Y9cF6LI\n9n1K9Z5EgoZ487LCIpMMjzI2hVeITJwUXMJiCWbW6JwbGPX4P4FzgZHAn5xzJxemibupWIIUSllN\nyo8RCRLCGrRm275SeG/rmMr8OMMB6+hNA5e2Pd64cSNNTU1s3bqV/fbbj379+pXefKBcSjXsLV+T\n1HM1CTvT43RmuF/YClEUouBCISQqolHo85dKifF8Cfp9krSlWywh2f+Ie5pZhXNuF4Bz7lYzWw3M\nBbrlqJ0ioZRsUn6pV7oL+5o/2bavFN7buHPyPtlF3d+a4Mjmtv+Ye/bsSc+ePYNqZnFJZ22WfGVc\ncpW1yOQ4nV2TJt41qDA4aH8YdXbhbwyLYQ5QOoLM8BRqPadSoExcyUlWNe4Z4PPRTzjnHgC+B3yS\nxzaJBK6sJuWXmVJ4b9vm3TkDoPKTnXRraWX8N54M5xophZDt+h7pVITK53yTeNXkCnGceP3+aBOc\nd3X8axjvGvTsDgsez67dmSqGOUBhp2poUsYSBkLOufHOuT/Hef4559wx+W2WSLDKalJ+mSmF97at\nBPrcT6ibt476yW+waMB0qt7eVJ43MLkoYpBOoYF0JqlnGpAFtVBjvH4DLHkz/jUM20T9sLWnGKka\nmpQxDRYXiSPsRQMkc6Xy3lbRg0njXus4PyIfNzBhnz+QSRGD2D6deGR6Q6ySDY3JdIhRkEOT4g0t\ni0h0DcM2PChs7Sk2pTK8UCQDWlBVJI5ki45KcSup97YQ5VzzVTI6lzr7jXa8Pj05G/bZK7shVpkO\nMQpyaFJkaFk8ygqkJ6hsXq5oeKGUMWWERBLIdlJ+0ZRoLkNhLwiRUiSbMXehN1G9axfYsTM/NzD5\nKhmdSmeyUJ39Rjten7Zsg0vOg+77Zl6wINMhRkEOTYoMLTvvam84XDRlBVIrhUIDxVBiXCRP0gqE\nzOw0oG/09s65h/LUJpFOCWPAEVuiuZG1TGVZ8WYeJDxib7y6doEuFXDSMTDs5NzfwARxk97Zm8vO\nru+RqE/L3tpdcjmT4YCZDjEq5NCkRP169u74pbeVFUguqC8Kck3DC6VMpQyEzOxh4CigEYiszOcA\nBUISuLAGHKVQollCKvbGa8dOMPOCoHzcyAQxf6CzN5ed/UY7VZ/SDcRig4qvXZDZgouFWqgxVb+U\nFeg8FRoQKWrpZIRqgRNdopVXRQIU1oCjFEo0l7SwT/5PptA3XkGspp5JHzvzjXaqPqUTiCUKKmZO\nhkee6Vww0dkgJNPPb6p+lWtWIJvfByo0IFLU0gmElgK9gSKb/SflIKwBR9wFL4usRHNehCEAKeSY\n/nz0t9A3XkFkCvLdx1R9SicQSxRUPPJMZsFEukFINp9fZS86yvb3QRBfFIhIzqRTNe4g4HUze97M\nno78yXfDRNIR1jVh2ha89NtWrCWacyos1ccKVaErX/0NosJTrhb7TFch+pisT+lU4wsqqMjm81uI\nKoNBSFa1LVVFt2x/H2gdI5Gilk5G6OZ8N0IkU2FdEyZSonkC85nHGupCUsQhUGGZVFyoG9h89bcY\n5nJkmwkLuo/pfMsf1JCobD6/pZi9SJbRgdTZnlz8PijXIYUiJSBlIOSc+6uZHQJtd5bznHNr89ss\nkfSEOeAophLNBam8F5ZhOYW6gc1nf/N945VNIBPvxvThp+FLw+H1t9I/XpA3l+kEYtkEFZle36Zm\n2La94/Ppfn6DDjDzIbHKVQYAACAASURBVFVGJ9WXEZrjI1LWLFUNBDMbBdwOzAEMGAaMc849kffW\nxaitrXULFiwo9GlFSlps5b1IVi3nlffG3uIND4u94agfVdgb3tgb9cgNbK6Hs8TrL0D1sV6p4lyd\nK9fzkLK9Pon6XWGwy+Xvegchcu07E1TEXl8z79p87QL46TXJCyQMuBA2f+xVCozo2sVb+6gUrmcm\n6kZ7Q087PF/t1bdN9Fp0mfRC/D4QkYIys4XOudpU26UzR+g/gcHOuSucc5cDdcBN2TZQRMIhWeW9\nnArL6uWFGtMf6W/XLu2fX7Yid3OjMp2HlGzeRLZzJuJlwsALgjI5XhBSzSuJyGTuVOz1dQ527vKy\nZsneu8h+0UEQwAlH7f78ptvuVHJ1nEJINu8pnTlRmuMjUtbSyQgtcc5VRz2uABZFP1coygiJ5F4d\nU5kfp8peHb1p4NLcniyTb9CLWVMznHc1LHmz/fNRmbCshiVmkmVL9Q14sm/YI9+iJ/P1H8CDT6Xe\nLt3jFVq+MwSJri+0f+9iM30vLoRF/4xzPP865qrdhciQRPftxCO95zozbDLd9oKyPSJlKt2MUDrF\nEp4zs+eB3/uPRwP/l03jREpZQebb5FBnS31n1b9ym1Rc1Qf22rPj8/5coawXBM5kHlKqIg7Zzpn4\neGvqbVIdL93hfvkoT57voh7xrm9E5L2LN8+qwrzsYnRGKPo65qrd+e5/bN+ig8JMStmnmvdUanOi\nRCSn0imWMM7MvgIM9Z+61zk3Pb/NEilOmdzYBh04dabyXlY37mFYQygISQKLrBcEziRoSRU8ZVsE\nYPqfk2+T6njpruuSr/Wg8l3UI3J9N2z2hsVFi7x38YKRrl2gS4U3pyje+5Jtu5ua4aY7vLbFDr/L\nZf9j+xZ7nkyCrmRfsOTry5dy/X0mUmLSmSOEc+4Pzrnr/D8KgkQS6Ox8m0hgMZnFzGcNk1nMAB6i\niU0Fa3Ok8l49NdTRm3pqEgY2Gc8nCssaQkFIMjcq6wWBM5l3lWreRDZzJiZM6XhzD16Znepj0zte\nunOU8rUeVL7X2olc38tHeoFNhe0+R+S9ixfU7NgJxx/Z8X0Bb4jkO6t3H6uz7W5qhuovekMaY4Og\nyHFOODI384YSzSGLKIYFXsv595lIiUmYETKzl5xznzGzzXi1V9peApxzLrxjfUQC0tkb26wzAjmS\nbqnvjG/cw7KGUBCSDN3p7LDEzhw7oXQyPpl+i96wZHdRhGgVFelXyksns9HUDNOey0/mphBr7VT1\ngQd+7lWJi/feJcr0DTze+3vkEr+3Fs6pj59h6Uy7J0zxqtHFU2Gwz17w5GzYsi377FuyoYGRdoe9\ndHU5/z4TKTEJAyHn3Gf8n90L1xyR4tbZG9usMwIFlvGNe1jWEMqXVMNkEgQWOVkQuLNBS2eCp84O\n/4l3kxspDZ3uDXOq4X6Rb+M3bu64by5uogu51k6i9y5eMBYvGPnN417Fuegsjhn0OgDO+Yz3+CvX\npn7vEgWwAAftD+cMg989m5sb/9i+RSuWBV5L/feZSBlJOUfIzI4CVjnntpvZGUAN8JBzbkO+GydS\nbDp7Y5t1RqDAMr5xL+VFC7OYqxLYgsDpBE+Z9CtRNuWn16TftlQZmci38bE37ma5u4kOuqhHvGBs\n88cdg5F4nIM+veDpF9J/74ZUw8Kl8a/pqLNze+Mf27cT/Kpxy94qnmIGpfz7TKTMpFM+uxGoBfri\nVYt7CjjJOXdu3lsXQ+WzsxP0pPxyEbnO6dzYFmwx0xzqTP9271TCixaGZaHYXMu0X7kokZ7sGInK\nTx98ICyYVvyfp0SSld2OVtnVm0v0xlvpv3eROUIbW9o/37MbLHnKey/y+RnPV+GBfB63VH+fiZSI\ndMtnpxMIveqcO9nMxgHbnHOTzOw159ygXDU2XQqEMleMN9zlIpPAoiiD2lJdQyjbdXfCKqz9KoXA\nM5Mb9LG3wD2PxS9mECmrHbkhr+oDi5OsOZSoTTfdATNfApw3HO6n1+xeqDVfN/65PHbs+kTRQwlz\nHayU6u8zkRKRy3WEWs3s34ArgAv85yqzaZwUXlgm5UtH6RYqiMh67Zk4xytIUBX0cKN8KdVhMunM\n1Ym+mf/aBfDIM9l/+54qSChEMYNcidcXyGwo5fgx3pyg2ECoSwWccBTsvefuG/IJU2DZivbvndnu\nYWjxRAo4JHotX/OmMi08EO/zF104YsHS9hUMY4+bbbaoVH+fiZSZdDJCJwLfBv7mnPu9mfUDRjnn\nflGIBkZTRihzdUxlfpwJ+HX0poFLA2iRdFYkYJnGm6xjS7tSjpVUUE9Np4NaZQpzoFSHySTrF7R/\nrWsX2LkTusRkJjp7DdK9lsXwbXyivoz8XPu5PpB+RmvAhellelINdQvTtcok8xjv2lZYx8IRcc9X\nDU/8T2n+mxWRNulmhFKuI+Sce905d41z7vf+47eDCIIkO0PoTWXM2x3mSfnSXvR6Q2tjgiBIXmmu\niU2MZTZ1TGUss9utUZTpukDJjll2sll3J8yS9Sv2W/wdO72SzpGb0EzX9El3baDIt/ENj3k/w3it\nE/Vl5ovxCw+8uDD1Oj2f/XR6axxV9YEvDe+4rtCWbdmvs5RrmazbFO/abm9NHQQlW7A2F2tQiUjR\nSadq3FDgZuAIf/vIOkJJcuwSNjkp0yuBiQ1YYiUKalMNo8ukfHeuh+blWy6G/qU8RqkOk0nUr1SL\nYkJmVcVKqSxxor5g3g159Gtdu3jFDV5fkXy4XGeGBb7+VscqcGG8lpkMdUzn8xdRYd51iD7uV64t\nnc+ZiGQlZUYImAL8CvgMMBivgpzunotMpExvPTXU0Zt6akJ741pukmVXIq/9lqVJg6BEQW2qjE8m\nmcJMs0hBiM6kzWcNk1nMAB7qVAYrF8coOfG+xY+VyTypTLIDYZWoL+d8xrshj7xW2dWb57NzV3qZ\nsHSzj8VyLTPJqCbq256V7a9rz25w2ciOxy2WayPBa2pOnamVopbOHKEG59yQArUnKc0RklKTbI4O\n0O61WBXAQezNKI5LmOVINTcskzlCyY75BBeEqprdWGYzmcUd1mnqzHyqXByj5MTO0Sj0HKFikGqO\nVfQcpxcXwqJOVnlLde6b7vCKVzjXPiOSr2vZVnXuRe9xdNW5fJwr3rWdOdnrczoLBZfK50zyR5+T\nopbLqnEvmNntwB+B7ZEnnXOvZtE++f/t3Xl8HOWd5/HPo8MHvrixAyLEJAEDtghgOUAMCUwCDAnG\nkMWvAUISPME5UIaZ2WiYhOyEibO7mOwOx7CJIQzhEDMwEwgYliselhCI5QMsCyxOcTRExtzygW0d\nz/5RKqnVXd1d1V1dVd39fb9efslqt6qf6irbz6+f5/k+IhQeXclVBLkFy1rOz1toFNqwtZgNPXMd\ncxZ7Jm7KXDFT/8pxjKrjlSLmpsaVEmBQznSyqBU6l/Qph61LR6fFuYodoUjvvA0OOWlx9XVw7unl\nLUwywxluvseJry5HOEO+93Zec2k/L+IqNtFQKoqfQsgdDUqvqixwUvjNEakt+TrZdvj3mSbRwDc5\nwtdoi5+1YUHju3MdE0hcRHuhQjCqY1Qlr/VDfjqhxRy3UuU6F6/o57AiwTM7b9ZCXT1MmVS+jv6y\nG6FvW/bjW7aVr9NY6n1STfeZlEc1rVmUnAoWQtbaL0TREJFaVKiT7fVn3+SIvIVF5sL+BziL2+gO\ntGFrPrlGkc5mRTgjJyHuBh9GSEhYQSMVuQmuhC9zuo0bjOB3WlchcXTeOrrG7tnjGrL+XzfEv/ci\noajWPeJkDD+pcfsB/x34mLX2tOF9hY611ipnUqREhTrZQTvgUSW6eY0ihTJykquTWOSc7GKm/vk5\nxvnMClTUZF2XgV7at6+l88oBmi66sLo7fOrgjrXsRmekJDNq/LYV4YxQxNF5mzc7ewNTcBLb/Lxu\nyH/vE6va/y5U2/lV0ubNUjQ/YQkPADcBP7LWNhtjGoCnrbWRl8QKS5Bq5I4UeHXU8/2ZlzgX9oey\nOWvrUlh+Z3GbTUakmPP0vC67Bllywwtc++Nnou/wRdVhKbSoPcjrV0sn68iF3sEIzYfC+ruyHw96\n3nEs8C51A9cK+HtfsmpfeF+t51cJmzeLpzDDEva21t5pjPl7AGvtgDGmwK5l/hhjTgWuBuqBX1lr\n/2cYxxWpJPnW6ARdvxPnwv4wRl8qYU52voCL9GuVPhXuNfqyr8u4elYfs1f0i2+j/PQ912LjEy9w\npk35ff1qGjHI3Ntn5HGPePxizrvYIIBSCs2mGU7BM5IaZ5yYcL/hDBXw975kYS28T+oHAtUaLKC1\nZFXPTyG0zRizF05AAsaYzwIflvrCxph64Drgi8AbwBpjzL3W2o2lHlvEVWvrMuJe2B+0cMuUOmUO\ny74+hY5j9mbe6s20Leui6a2dsc/JLljUZBSbmaNGxuOYjbsGaVn9dvQdvnJ3WNI7aj2pHJuKZnxf\n6PW92rxlG5z+HZgwvnCHsMTOY9H/jni9rvG6G3CmkWUq9lrl67x5tQlKLzSbZsCv/4e/52a24bCZ\n1b8WI4xiL7MwXvsM/OLfnLCNciUC+lULxaxUJT+F0N8A9wIHG2OeAPYBvhrCa7cAL1lrewCMMf8G\nLABUCEkoyr1eJolFVlgL++OQoo/my6ewdeAQ+sfVsf4ze9J+/ifpPOERmmKck+2rqMkoNjNHjdwx\ngLohy1CdoXHXIJO3DtC2rCv6Dl85OyyZHTW/Cr2+V5sHBqHrBef3+TruJY4mFf3vSK7XPeML8OyL\nTrS1q74O5h/t77xLuVb52hTVp/lebdhtgvNr+47qXYsRxtotr0TAQQu33gv3PhrvCKmCBaRC1RV6\nwvB+QScCxwFLgMOttRtCeO39gVTa928MPyYSikJ79JTC7RwtZwNr2MRyNtDMLaToK/nYpXCnpy1h\nDi1MZwlzYt3HJ4hlrGFr3SD945x/lvrH1bN1yjiWPfk3sX7SmbOoGf7qVWx6TVEE2HtoAi3r3mXJ\nDS/Q2Xy3M9oVdYdv3myng5IurA5LZkfNS51xNmDNfP1ZM3Pv4O7V5nTpHfdCbcr3XK9TKvbfkVyv\nu+2j7GlwQ0POp/qZwr5Wudr0wOPRfZrv1YbtO+DMk501QS2zna+VOO0xn7bFzt9193oWU+x5Fcbg\nTLcMcE+XRRjnJ9FI9eb+t7YG+UmNqwf+HDho+PlfMsZgrf3fZW6b+/oXARcBHHjggVG8pFSJcq6X\n8btOJA6lTk+Ly+95M/t6NRhWT4m3uMxZ1DCRg5jmuRYq1xTFcxpmce2+Z8NzN8LHtsCZEczxL+ee\nNZlyddTSHToTet8e+/q7TXA233RHBDJHbTLTm7zk6riXOKpS9L8juV7392uhvn40NQ6gocEJj8jc\nhyloalWhKYC52oRxjh3Fp/m52tDdAx13hP96SRHGJq5eoy6uuKehaZPaylCO9ZZJXbfmk5+pcSuA\nHUAXePQGivcm0JT2/QHDj41hrb0euB6c1LgQX1+qXDnXy8QZSlCNUvTxPO9lPd6AiX3j0pxFDYfk\nLDjzTlFsmhp/MEJYe9ZkytdRA6dzfdI85/XSO0xbtsHt9+eempXZyfpoJ3S/PLaYyNVxL3HKTtH/\njuR6XRjbbvd8vTqxQTqXfjo4udp02uecqVVRxATX8hSqUhfeu4XxB1uyo8qT8B4qWCD5wl4jWgVB\nNn7iszdYa+eE/sJODPcLwMk4BdAa4Fxr7bO5fkbx2RJEKHHOOcQZU12NWlnJL+lkgLH/Ho2njhdZ\nHOvUvmLvo6DR52URdSxxvjVC+eJ0WxbBGo9CoGW29yhBkKjeEmN9i/53JNfrnvGFsUWf+96Uek28\nrnWdgb33gHNO9Q5FSH8vIJpP873el90mOFPjNvZU5CfKkUr1Oul8t61wiqEhWz1R1VJ+Qf+tLSTB\n0fd+47P9FEJXACuttQ+H1bi0Y/85cBVOfPa/WGt/lu/5KoQkqHJ1RstZZEUhaUEPLbSzxmM0rZl9\nWM8FMbRorEQUNcUI+z89P9L33Zg103msuyd/57qY/0zdDuEDfwAsnDY/d3KW371AckzxKPr6e70u\nlGe/lVzXGuIpePLJvEfSp0WWstdUEkS5R1fc11EqT9iFSxz/x/gUZiG0ELgNZ21wP2AAa62NvBeg\nQkiSpFI7x0kr4lL0cTp308U7Yx7XCFsI4hgRKqYTWMyoTdgbOEa5IWQ5OrFe1zqd13WPc26/+9p3\nPghvvz92qldDvZOk5+41VSkjHtW6qahUj7Dv0RoZEXoFJ9a6yxZ6cpmpEBIpXZKm9blF2RZ2jZkW\nF3dxVjX8/qcXRoe41P9gg4zwQPj/ASf4P3Rf/ESXp39Km/l8Y5ypdFHsSVNMzHolXItKv4ekNoT5\nQUyCi3+/hVDB+GyciOtn4i6CRCpJij5aWUkL7bSyMvZY7XRJCnpw0/cy1wYdyp4qgsLgLrbPF0vs\n/ke2/E5nisPyO53vg0aqlhhTDTgL9t//EDa/56yjydeOXOljdz5UXCxsruM9vq4yombTr/W+e2Vv\n3Jq5mN5zT5ohZ0+azPc97LhdPzHrmeJORfNDm4pKJXBDLTruGA2jKeVYhf6PSTg/qXE9wP8zxjwA\n7HQfjCo+W2pL0tauFKPQBoyh7lJfxD825UzTCypXNPVEGiruuidWoSSnsFKEPDqBqf3Gs2z+h3TQ\nXvheD9qOXAl1b78Hm98Nnl7kdbyGeniuBza+XBmJSO61blvs/Sltegqcnz1prr3M+Xdn9gIn2W/I\nwrpnnGKp657i34N8MeuNDc7I1OCQv1TAJKnlRDypXRWeFuhnROgVYCUwDpiS9kskVEndpDTo6E6+\nPYaKPsewPrXHiXaeTCONw3/9vTYEjco8po+0wxVXUeZXkkf7ihLWp9gZm3+mDphE84aFLD9rP3/3\netB2ZG7gWDc8AuJOXkgvpPyMaHhtCFlf53TISxnlCkPQERk/n9Lm26Q2/X3/8TXw4VanCALn64db\nnceL5fXadQb23dNp62O3wJRJlbc5pzYVFak4BdcIJYnWCFW3JK1dcRUTLJArAa2F6bQwvbhzDHnu\neVKCHpIW3FBIIttb6khhWPdWxlzx1n8+juXfOoT+caOFbt57vdjkOHeu+6tvOlPqMjUfAq/3+o/a\nTp87//g66Hw++5hRJiKVaw6+e9wP+sCrG/D1BfDr/wH7fc7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WtO1/8Rd/wVlnnTXy/c9/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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f5e4440c750>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 根据‘Channel‘数据显示聚类的结果\n",
    "vs.channel_results(reduced_data, outliers, pca_samples)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 问题 12\n",
    "\n",
    "*你选择的聚类算法和聚类点的数目，与内在的旅馆/餐馆/咖啡店和零售商的分布相比，有足够好吗？根据这个分布有没有哪个簇能够刚好划分成'零售商'或者是'旅馆/饭店/咖啡馆'？你觉得这个分类和前面你对于用户分类的定义是一致的吗？*"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**回答：**\n",
    "\n",
    "我选择的是高斯混合模型聚类算法，分成了2个聚类，与内在的旅馆/餐馆/咖啡店和零售商的分布相比，足够好。\n",
    "\n",
    "根据这个分布，旅馆/餐馆/咖啡店基本都在 Cluster 0 里，零售商基本都在 Cluster 1 里。\n",
    "\n",
    "我之前定义 Cluster 0 为饭店，Cluster 1 为超市，与现在旅馆/餐馆/咖啡店和零售商的分类基本一致。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "> **注意**: 当你写完了所有的代码，并且回答了所有的问题。你就可以把你的 iPython Notebook 导出成 HTML 文件。你可以在菜单栏，这样导出**File -> Download as -> HTML (.html)**把这个 HTML 和这个 iPython notebook 一起做为你的作业提交。  "
   ]
  }
 ],
 "metadata": {
  "anaconda-cloud": {},
  "kernelspec": {
   "display_name": "Python 2",
   "language": "python",
   "name": "python2"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.12"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}
